bluuebunny/crossref_metadata_2025 huggingface dataset:
Wnt/pathway, APP processing and telomere shortening in Down syndrome adults
Authors: Cordeiro Augusto Magno Tranquezi , Bram Jessyka Maria de França , Talib Leda Leme , Forlenza Orestes Vicente , Fernandes Lillian
Published: January 2025

Background

The Down Syndrome (DS), also referred to as trisomy of chromosome 21, is a prevalent cause of intellectual disability and also contributes to the acceleration of aging, among other developmental and health concerns. Certain pathological characteristics shared by DS and Alzheimer’s Disease (AD) indicate similar commonalities.

This study aims to unravel the relationship between the canonical Wnt/pathway, the amyloid precursor protein processing, the telomere shortening in DS individuals. The telomere is a structure found at the end of the chromosomes that protects against degradation during cell division. The shortening of the telomere length is associated with the risk of AD. β‐catenin is an important factor in the canonical Wnt pathway. The activation of this pathway can protect against neurotoxic effects caused by accumulation of β‐amyloid peptide and the phosphorylation of Tau protein. The canonical Wnt activation is related with the activation of subunit Tert, also known as telomerase. Telomerase is an enzyme responsible for the maintenance of telomere length.

Methods

The biomarkers were quantified in the plasma and platelets of adults and elderly with DS (n = 55) and adults and elderly without DS (n = 80). We utilized western blot, for APP fragments (110 kDa and 130 kDa), Luminex xMAP, for AB40 fragment. The DNA was extracted from leukocytes and measured using qPCR method using 36B4 as single copy gene. Telomere length was calculated using the delta Ct value.

Results

We found increased levels of Aβ40 and in 110 kDa, 130 kDa APP fragments of Down syndrome individuals. β‐catenin was also increased in DS group when compared with non DS group. The telomere length was decrease in DS group when compared with non DS group.

Conclusion

The increase in Aβ40 and 110 kDa, 130 kDa fragments, demonstrated an imbalance in the APP processing, that could lead to the Aβ aggregation observed in DS individuals. The increase in the β‐catenin expression could be a compensatory mechanism for the telomere shortening in DS group.
Functional connectivity changes through Alzheimer’s disease continuum: disease onset, progression, and response to therapy
Authors: Zimmer Aline R. , Bourourou Miled , Lesage Frédéric , Hamel Edith
Published: January 2025

Background

Hemodynamic signals are the basis of functional brain imaging techniques, such as fMRI and NIRS, and are often used to infer changes in resting‐state functional connectivity (RSFC) in Alzheimer’s disease (AD) and other dementias. Increasing evidence suggests that disruption of neuronal circuits has been associated with the AD continuum and may precede changes in Ab and tau biomarkers, neurodegeneration, and cognitive impairment. To better understand the changes in brain RSFC through the AD spectrum, we use hemodynamic signals to detect disease onset, progression, and response to therapy in a mouse model of AD.

Method

Hemodynamic signals were recorded longitudinally (3‐8 months) in anesthetized (ketamine/xylazine) and awake WT and APP (J20) mice, implanted with full cranial window, using optical imaging of intrinsic signals (OIS), together with cognitive testing. Seed‐based functional connectivity maps were generated for the bilateral connectivity (BC) and RSFC analyses. The effects of simvastatin (SV), a cardiovascular medicine that has shown promise in preventing dementia, were evaluated after 2.5 and 5 months.

Result

Alterations in RSFC in brain regions associated with the sensory‐motor (SM) and default‐mode (DMN) networks were detected before the appearance of cognitive impairment. 3‐month‐old APP mice showed consistent decrease in bilateral functional connectivity (BC) in motor (M) and cingulate (C) cortical regions and a severe hypoconnectivity within the SM network in the RSFC analysis. Throughout the course of the disease, RSFC analysis in APP mice uncovered an early hyperconnectivity within the DMN, mainly driven by the frontal (F) cortex, followed by a later hypoconnectivity stage. At late stage of the disease (8‐months‐old), a decreased BC in somatosensory (S) cortex was detected. SV treatment prevented the aberrant increases in DMN FC in midlife APP mice, improved the BC of S cortex, while concurrently sparing cognitive function.

Conclusion

Our results demonstrated that hemodynamic signals measured by OIS at the cortical level successfully detected RSFC disruptions preceding dementia in APP mice and allowed to capture SV therapeutic benefits. These findings suggest that OIS, or its human equivalent NIRS, could contribute to effectively diagnosing the early stages of AD, leading to promising intervention opportunities.
White matter aging in late midlife women: Validation and association with neurodegenerative biomarkers
Authors: Li Jinghang , Wu Minjie , Chen Chang‐Le , Wang Linghai , Yang Shaolin , Aizenstein Howard J , Chang Yuefang , Karikari Thomas K , Derby Carol A. , Maki Pauline M , Thurston Rebecca C
Published: January 2025

Background

Brain age (BA) prediction models have emerged as valuable tools for understanding individual differences in trajectories of brain aging. These models aim to estimate overall brain health by predicting BA based on structural MRI data. To enhance the specificity of existing BA models, we introduce a deep learning‐based BA prediction model. The model focuses on the cerebral white matter to assess the prominent cerebrovascular AD risk pathway for women. Here we validate our deep learning‐derived white matter brain age (WMBA) in a sample of late midlife women enrolled in MsBrain. We also examine WMBA in relation to plasma neurodegenerative biomarkers in this sample.

Method

We developed an age‐conditioned variational autoencoder along with a multilayer perceptron (MLP) for brain age prediction (Figure 1). The model was trained on the Human Connectome Project healthy aging (HCP‐A) dataset (female, n=396; male, n=316, 36‐90 yr, mean=60 yr). To achieve white matter specificity, the model was trained only on the myelin ratio map. Adaptability and credibility were assessed by testing the model with MsBrain data, a study for which midlife women with no cardiovascular disease, stroke, or dementia were recruited (n=239, 45‐67 yr, mean=59 yr). Plasma biomarkers included amyloid β (aβ) 42, phosphorylated tau (181, 231), glial fibrillary acidic protein (GFAP), and neurofilament light (NFL) via Simoa. All brain age predictions underwent bias correction through fitted linear regression models.

Result

Figure 1 shows the overall WMBA model schematics, including myelin ratio map training inputs, brain age predictions, and generated WMBA outputs. Compared with chronological age, the WMBA model was more strongly associated with cerebral white matter volume (Figure 2a). When considering brain age gap (i.e., difference between predicted brain age and chronological age), a greater brain age gap (indicating older brain age) was found with lower cerebral white matter ratio (Figure 2b). Lastly, greater WMBA was associated with higher GFAP and aβ42.

Conclusion

This work validates a new approach for measuring WMBA and demonstrates its utility in studies of midlife women. Findings indicate that WMBA varies with plasma markers of neurodegeneration in late midlife women, suggesting a novel neuroimaging marker to detect early neurodegenerative changes.
Quantification of PET amyloid [18] Florbetaben using the Centiloid Scale
Authors: da Silva Maria Rosa Alves , Aguzzoli Cristiano Schaffer , Garrafiel Fabricio Nery , da Silva Ana Maria Marques , Schilling Lucas Porcello
Published: January 2025

Background

Alzheimer´s disease (AD) is the main neurodegenerative disorder and leading cause of dementia. AD neuropathology involves the extracellular formation of senile plaques with β‐amyloid peptide and intraneuronal tau phosphorylation, leading to neurofibrillary tangle accumulation. These can be detected by biomarkers obtained from cerebrospinal fluid or Positron Emission Tomography (PET) using specific radiotracers. Amyloid PET results can be interpreted by standard uptake values (SUVR > 1.42 positive or < 1.42 negative) or by the Centiloid scale (CL) which anchored from 0 to 100, classifying low βA uptake (<30 CL), intermediate‐high βA (>30 CL and <50 CL) and high βA (>50 CL). The aim is to analyze the distribution of CL values in [18F]Florbetaben (FBB) PET images in a sample of DA suspects.

Method

A retrospective study was carried out using 28 anonymized images of FBB amyloid PET. The PET images were obtained using in the PET/CT system and the Magnetic Resonance Imaging (MRI). For this study, T1‐weighted structural images were used for co‐registration with PET images and normalization with the CL atlas. In this study, the images were processed using PMOD software with the PNEURO tool.

Result

The implementation of CL required reproducing the image processing steps with the GAAIN dataset. A total of 28 participants were included in our study and Figure 1 shows the graph of this investigation. In Table 1, when analyzing the CL, the data shows a varied distribution: 8 participants below 30CL, 9 recorded values between 30CL and 50CL, and 11 presented values above 50CL. Figure 2 shows an example of a positive and negative individual. The analysis of the distribution of individuals with different stages of aging in CL allowed us to investigate how the use of different cut‐off points for the βA classification can have an impact on the diagnosis of AD pathology.

Conclusion

The use of the CL is an accurate and robust method to evaluate amyloid deposition in the brain. The communication of PET scan results with the CL scale also allows normalization for any amyloid radiopharmaceuticals, making it more suitable for analysis of disease progression and response to treatment.
Cognitive outcomes with AD tauopathy characterized by florquinitau PET
Authors: Bahr Melissa , Wintlend Madilynn , Mandel Olivia R , Studer Rachel L , Jonaitis Erin M. , Alberson Sara Frost , Meyering Emma , Ryther Brenda , Hellenbrand Teresa , Kaminski Noelle , Chin Nathaniel A. , Betthauser Tobey J. , Christian Bradley T. , Johnson Sterling C.
Published: January 2025

Background

PET imaging studies examining amyloid‐β plaques and tau neurofibrillary tangles, concurrent with cognitive testing, give insight into in vivo Alzheimer’s Disease (AD) pathology burden and corresponding clinical outcomes. Braak stages IV‐VI indicate advanced tau aggregation in the association and primary cortices associated with AD neuropathological changes which are often accompanied by cognitive decline or impairment. Not all individuals with AD pathological changes present with the expected rate of cognitive decline or standard Braak staging progression, such as in cases of resilience or posterior cortical atrophy (PCA), a variant of AD identified by parieto‐occipital tau aggregation.

Methods

Tau PET data were obtained from two Wisconsin Alzheimer’s disease cohorts (N = 830). Participants were assigned to a Braak stage if they were positive for tau in that region and all prior regions (cumulative deposition), and those in Braak stages IV‐VI (N = 112, Table 1) were included. Chi‐square tests were completed to examine the relationship between Braak staging and concurrent research diagnoses. Participants with non‐cumulative deposition were excluded (N=40); two with non‐AD‐like patterns are described.

Results

Of the research participants with a tau PET scan rated Braak IV or higher, 71.4% were impaired (Figure 1). Diagnoses differed significantly across Braak Stages, χ2 (4, N = 112) = 30.8, p = .00050. Specifically, Stage VI differed from IV (p < .001) and V (p < .001).

We present 2 individual case studies of participants who deviate from this pattern (Figure 2). Case study 1 presented without cognitive impairment, despite tau PET scans rated as Braak VI. Case study 2 presented without cognitive impairment and predominant parieto‐occipital tau burden suggestive of PCA. The tau depositions in the presumed PCA case initially localized to the medial occipital region and spread in reverse hierarchical order of tauopathy in all regions over 5 years.

Conclusion

This analysis of tau PET data supports a relationship between the visual read estimate of tau burden and cognitive change. Continued research on the heterogeneity of disease progression, such as presented in these case studies, is important to further our understanding of disease development, resilience factors, and clinically relevant outcomes.
Voxel‐wise comparison of [18F]MK6240 and [18F]Flortaucipir for the diagnosis of individuals across the Alzheimer’s disease spectrum – the HEAD study
Authors: Bellaver Bruna , Povala Guilherme , Bauer‐Negrini Guilherme , Lussier Firoza Z , Amaral Livia , Ferreira Pamela C.L. , Lowe Val J. , soleimani‐meigooni David N. , Oh Hwamee , Tudorascu Dana , Jagust William J. , Klunk William E , Pascual Belen , Gordon Brian A. , Rosa‐Neto Pedro , Baker Suzanne L. , Pascoal Tharick Ali
Published: January 2025

Background

In vivo studies using the tau PET tracers have shown high performance for the diagnosis of Alzheimer’s disease dementia and patterns of tracer uptake that resemble those observed in post‐mortem studies. However, tau tracers present distinct patterns of binding that might influence their performance in detecting AD pathology. In a head‐to‐head study, we investigated the performance of [18F]MK6240 and [18F]Flortaucipir for the diagnosis of AD.

Method

We assessed 132 individuals from the HEAD study (58 CU Aβ‐, 15 CU Aβ+, 14 MCI Aβ‐, 32 MCI Aβ+ and 13 AD dementia) with Aβ‐PET, [18F]MK6240 and [18F]Flortaucipir. Voxel‐wise receiver operating characteristic curves (ROC) of the two tau tracers were used to contrast groups provided the area under the curve (AUC) for disease diagnosis or biomarkers positivity.

Result

The brain maps showed numerically higher and more spread AUC for [18F]Flortaucipir to discriminate CU Aβ‐ from CU Aβ+ (Figure 1A). The difference between tracers’ AUC was greater in Braaks IV and V (Figure 2A), both regions that are not expected to have tau accumulation in CU Aβ+ individuals, reflecting a potential off‐target binding for [18F]Flortaucipir. To differentiate CU Aβ‐ from MCI Aβ+ individuals, [18F]MK6240 presented a numerically higher AUC than [18F]Flortaucipir in Braak I and II and similar AUC in other Braak regions (Figure 1B, 2B). We observed a high performance of [18F]MK6240 and [18F]Flortaucipir in differentiating AD dementia from CU Aβ‐ individuals. However, [18F]MK6240 exhibits a higher AUC than [18F]Flortaucipir in all Braak regions, especially Braak V‐VI (Figure 1C, 2C). Finally, [18F]MK6240 presented higher AUC in all Braak regions to discriminate MCI Aβ‐ from MCI Aβ+ individuals (Figure 1D, 2D).

Conclusion

Our results indicate that [18F]MK6240 and [18F]Flortaucipir present high accuracy to discriminate AD from CU Aβ‐ individuals. However, [18F]MK6240 presents higher AUC to discriminate AD and MCI Aβ+ from CU Aβ‐ individuals than [18F]Flortaucipir. Together, our head‐to‐head study sheds light on the distinct patterns of binding for Tau‐PET tracers.
Neighborhood disadvantage and ADRD pathology assessed with plasma biomarkers
Authors: Dube Samriddhi , Powell W. Ryan , Buckingham William R. , Yang Kao Lee , Johnson Sterling C. , Ashton Nicholas J. , Blennow Kaj , Zetterberg Henrik , Kind Amy J.H. , Bendlin Barbara B.
Published: January 2025

Background

Neighborhood disadvantage as measured by the Area Deprivation Index (ADI) is associated with Alzheimer’s disease (AD) pathology at autopsy, as well as neuroimaging measures of neurodegeneration. Plasma biomarker assays have emerged as an accessible tool for evaluating ADRD pathology, opening up the possibility of better understanding the effect of neighborhood disadvantage on brain disease among a broader group of research participants. In this study, we evaluated whether neighborhood‐level socioeconomic disadvantage is associated with plasma‐based biomarkers of Alzheimer's disease and related pathology.

Method

The participants were 371 individuals enrolled in the Wisconsin Registry for Alzheimer’s Prevention (WRAP) study and data included 1095 unique plasma measurements of the participants. EDTA plasma was assayed for pTau 217, pTau181 and pTau231, neurofilament light chain protein (NfL), and glial fibrillary acidic protein (GFAP). Participants’ addresses, as on the plasma measurement date, were geolinked to their statewide ranking of neighborhood disadvantage using a time‐concordant ADI. We compared participants living in the 20% most disadvantaged areas based on state residence (ADI of 9 or 10) to all other participants (80% less disadvantaged, ADI of 1‐8) by fitting adjusted linear regression models. We used the age, sex and years of education of the participants at the point of sample collection as characteristics.

Result

Living in the 20% most disadvantaged neighborhood was associated with higher GFAP concentration, an effect that was marginally significant (b = ‐1.4898; 95% CI; ‐2.978 to ‐0.002; P = 0.050). No significant effects of ADI were observed on pTau 217, pTau181, pTau231, or NfL.

Conclusion

Living in the most disadvantaged context was associated with elevated GFAP, a marker of astroglial activation. Elevated GFAP has previously been associated with amyloid pathology and neuroinflammation. The absence of significant associations with ptau biomarkers here may suggest non‐amyloid related processes, although this study may also be underpowered to detect relationships with amyloid, and further investigation is needed. There is an opportunity for future research to gain insight further into the mechanisms responsible for this association. Leveraging plasma biomarkers, future studies can provide a mechanistic understanding for the effects of contextual disadvantage on ADRD development.
Head‐to‐head comparison of four different plasma p‐tau217 assays to detect brain amyloid pathology and cognitive decline in diverse population‐based cohorts
Authors: Deek Rebecca A , Zeng Xuemei , Gonzalez‐Ortiz Fernando , Balogun Wasiu Gbolahan , Ferreira Pamela C.L. , Bellaver Bruna , Chen Yijun , Sehrawat Anuradha , Lafferty Tara K , Povala Guilherme , Klunk William E , Kamboh M. Ilyas , Villemagne Victor L , Pascoal Tharick A. , Ganguli Mary , Zetterberg Henrik , Blennow Kaj , Lopez Oscar L. , Cohen Ann D , Snitz Beth E. , Karikari Thomas K
Published: January 2025

Background

Plasma p‐tau217 is a highly promising biomarker for detecting Alzheimer’s disease (AD) pathology. However, it is unclear how p‐tau217 assays from different sources perform compared to one another. Moreover, studies in diverse cohorts and population‐based settings are limited. We performed a direct comparison of four different p‐tau217 assays to detect brain amyloid‐beta (Aβ) deposition or cognitive decline.

Method

We included n=427 participants from three separate cohorts from southwestern Pennsylvania, USA. Cohort‐1 was the Monongahela‐Youghiogheny Health Aging Team (MYHAT, n=87, median age 83 [IQR: 78‐87.5], 74% female), an ongoing population‐based cohort drawn from a medically and economically underserved Rust Belt region. Cohort‐2 was the MYHAT‐NI sub‐study (n=111, median age 76 [IQR: 72‐80], 54% female), which performed two‐year longitudinal follow‐up neuroimaging assessments of Aβ, tau, and neurodegeneration by structural MRI. Cohort‐3 was the Human Connectome Project (HCP, n=229, median age 62 [IQR: 56‐70], 65% female) which targeted a 50:50 split of self‐identified Black and non‐Hispanic White individuals. Plasma p‐tau217 was measured using assays from four different sources: University of Pittsburgh (UPitt), ALZpath, University of Gothenburg (UGOT), and NULISA from Alamar Biosciences. Aβ positivity was defined as a mean SUVR > 1.346. Clinical Dementia Rating (CDR) and Mini Mental State Examination were used to assess cognitive performance.

Result

In the MYHAT‐NI cohort, three p‐tau217 assays—UPitt, ALZpath, and NULISA—were employed. The assays demonstrated equivalent AUCs for determining Aβ positivity, ranging from 0.84 to 0.90. UPitt and ALZpath assays also showed similar AUCs in the HCP cohorts, with values of 0.87 and 0.90, respectively. In MYHAT, the UGOT and ALZpath assays separated CDR=0 and CDR=0.5 participants with equivalent AUCs (0.79 vs. 0.81). Significant correlations were observed in all inter‐assay comparisons, with Pearson correlation between assays ranging between 0.40 and 0.86.

Conclusion

We observed largely equivalent performances of plasma p‐tau217 assays in predicting amyloid positivity and cognitive impairment across three diverse cohorts of community‐dwelling older adults.
Robust multi‐modality segmentation of medial temporal lobe subregions using both 3‐tesla and 7‐tesla magnetic resonance imaging
Authors: Li Yue , Khandelwal Pulkit , Xie Long , Brown Christopher D. , Lyu Xueying , Denning Amanda E , Dong Mengjin , Das Sandhitsu R. , Wolk David A , Yushkevich Paul A.
Published: January 2025

Background

Volumetry of subregions in the medial temporal lobe (MTL) computed from automatic segmentation in MRI can track neurodegeneration in Alzheimer’s disease. However, dropout artifacts are present in some modalities, leading to poor image quality and unreliable segmentation of MTL subregions. Considering that MRI modalities with different field strength offer distinct advantages in imaging different parts of the MTL, we developed a muti‐modality segmentation model using both 7‐tesla (7T) and 3‐tesla (3T) structural MRI to obtain robust segmentation in poor‐quality images.

Method

MRI modalities including 3T T1‐weighted, 3T T2‐weighted, 7T T1‐weighted and 7T T2‐weighted (7T‐T2) of 197 subjects were collected from a longitudinal aging study at the Penn Alzheimer’s Disease Research Center. Among them, 7T‐T2 was used as the primary modality, and all other modalities were rigidly registered to the 7T‐T2. A model derived from nnU‐Net took these registered modalities as input and outputted subregion segmentation in 7T‐T2 space. High‐quality 7T‐T2 images from 25 selected training subjects were manually segmented to train the multi‐modality model. Modality augmentation, which replaced certain modalities with Gaussian noise randomly, was applied during training to guide the model to extract information from all modalities. To compare our proposed model with a baseline single‐modality model in the full dataset with mixed high/poor image quality, we evaluated the ability of derived volume/thickness measures to discriminate Amyloid+ mild cognitive impairment (A+MCI) and Amyloid‐ cognitively unimpaired (A‐CU) groups, as well as the stability of these measurements in longitudinal data.

Result

Figure 1 shows characteristics of both training and test sets, as well as segmentation performance of models. The multi‐modality model delivered good performance regardless of 7T‐T2 quality, while the single‐modality model under‐segmented subregions in poor‐quality example images. The multi‐modality model generally demonstrated stronger discrimination of A+MCI versus A‐CU (Table 1). Intra‐class correlation and Bland‐Altman plots demonstrate that the multi‐modality model had higher longitudinal segmentation consistency in all subregions while the single‐modality model had low consistency in poor‐quality images (Figure 2).

Conclusion

Using multi‐modality MRI, we provide an automatic MTL subregion segmentation algorithm that is robust to image quality. Our findings can help develop improved imaging biomarkers for neurodegeneration.
APOE ε4 genotype confers risk for Alzheimer Disease in Cuban Americans
Authors: Sanchez Jose Javier , Akgun Bilcag , Hamilton‐Nelson Kara L. , Rivero Joe , Celis Katrina , Adams Larry D. , Valladares Glenies S , Silva‐Vergara Concepcion , Rodriguez Vanessa C , Mena Pedro R. , Whitehead Patrice L. , Prough Michael B. , Griswold Anthony J. , Dalgard Clifton L. , McInerney Katalina F , Vance Jeffery M. , Cuccaro Michael L. , Beecham Gary , Rajabli Farid , Pericak‐Vance Margaret A
Published: January 2025

Background

The risk of Alzheimer Disease (AD) conferred by APOE and other genetic factors differ across populations. The Cuban American (CA) population is 3‐way admixed (European, African, and Amerindian) and vastly underrepresented in genetic studies. Previous genetic studies in this population have solely focused on APOE in AD and shown conflicting results regarding its effects. We aimed to evaluate the effect of the APOE genotype and other variants in potential causative AD genes in the CA population.

Methods

The CA dataset includes Whole Genome Sequencing (WGS) and Array data from 141 individuals (40 AD, 50 mild cognitive impairment [MCI], 51 cognitively unimpaired) ascertained through the Cuban American Alzheimer’s Disease Initiative (CuADI). To assess the effect of APOE‐ε4 allele dosage on AD, we used a generalized estimating equations (GEE) method adjusting for sex, age, and population substructure. Subsequently, we extracted and evaluated all variants in 7 potential causative genes: APOE, APP, MAPT, PSEN1, PSEN2, SORL1, and TREM2. We calculated the admixture proportion using a model‐based clustering algorithm implemented in the ADMIXTURE software.

Results

The APOE‐ε4 alleles were significantly associated with AD risk (p=0.013; OR=3.4[1.3‐8.7]). The causative genes analysis showed a known exonic variant (rs117260922; p.E270K) in the SORL1 gene in 1 AD and 2 MCI individuals, and a novel splicing variant (c.308‐1G>A) in the MAPT gene in an AD individual. Admixture analysis revealed average proportions of 83.4% European, 12.4% African, and 4.3% Amerindian in the CA cohort.

Conclusions

We showed that the APOE‐ε4 genotype conferred a risk for AD in the CA population. The effect size of the APOE‐ε4 in our study was found to be similar to a recent study in large non‐Hispanic white (NHW) cohort (OR=3.32, Kunkle et al. 2019). High European background in the CA population is likely cause to this similarity. Our results also support that the E270K variant in the SORL1 gene, previously linked to AD in Caribbean Hispanics and NHW studies, contributes to the risk of AD. These findings provide new insights into the genetic architecture of AD in the CA population.
Sex‐dependent Biomarker Signatures in Alzheimer's Disease
Authors: Jain Lavanya , Khrestian Maria , Tuason Elizabeth D. , Pillai Jagan A. , Rao Stephen M. , Leverenz James B , Bekris Lynn M.
Published: January 2025

Background

Alzheimer’s disease (AD) is a pathologically heterogeneous disease making it a challenge to develop effective treatments. Emerging evidence suggests that there are pathological differences between women and men with AD. More biomarkers are needed to enhance sex‐specific precision medicine in AD. Cerebrospinal fluid (CSF) biomarkers for amyloid (A), tau (T), and neurodegeneration (N) can be utilized to more precisely define pre‐mortem pathological status (ATN research framework) to limit the heterogeneity of a study cohort. The hypothesis of this study was that non‐ATN biomarkers differ by sex and ATN in AD. The overall aim of this preliminary investigation was to understand sex differences in seven biomarkers in an ATN defined AD cohort.

Methods

Cerebrospinal fluid (CSF) samples from an AD/MCI cohort were obtained from the Cleveland Alzheimer’s Disease Research Center and Cleveland Clinic Lou Ruvo Center for Brain Health Aging and Neurodegenerative Disease Biobank. CSF Aβ42/40 (A), p‐Tau181 (T), and t‐Tau (N), were evaluated for ATN analysis. Only A‐T‐N‐ individuals were included in CN and only A+T‐N‐, A+T+N‐, and A+T+N+ were included in as MCI and AD (MCI/AD) individuals. Seven biomarkers namely, neurofilament light chain (NFL), soluble Triggering receptor expressed on myeloid cells 2 (sTREM2), Neurogranin, fatty acid binding protein 3 (FABP3), glial fibrillary acidic protein (GFAP), neuron specific enolase (NSE), and α‐synuclein (α‐syn) (were also evaluated. Statistical analyses such as ROC analysis and one‐way ANOVA were carried out in RStudio.

Results

This was a cohort of over 300 individuals out of which approximately 50% were females and 50% were males. Males exhibited differences between the CN (A‐T‐N‐) and MCI/AD (A+T‐N‐, A+T+N‐, A+T+N+) group for NFL, Neurogranin, FABP3, NSE, and α‐syn, whereas females showed for NFL, sTREM2, and α‐syn. When comparing ATN status between sexes, GFAP was found to be higher in CN (A‐T‐N‐) males and MCI/AD A+T+N+ males, and sTREM2 was higher in MCI/AD A+T+N‐ males.

Conclusions

These preliminary results show significant differences between and within sex for these selected seven biomarkers. With validation from a larger dataset and more robust statistical analyses, this could have crucial impact on AD related diagnostic and therapeutic approaches.
Developing an AI algorithm to detect predictors of poor performance in a self‐administered, web‐based digital biomarker for Alzheimer’s Disease: proof of concept
Authors: Butler Joe , Owo Adewale Samuel , Watermeyer Tamlyn J , Danso Samuel O. , Parra‐Rodriguez Mario A ,   Binding in Neuropsychiatric Disorders (BIND) Group
Published: January 2025

Background

The Visual Short Term Memory Binding (VSTMBT) task is a gold‐standard cognitive assessment for the identification of Alzheimer's Disease and associated risk factors, including during the preclinical stage. Previous work from our group (Butler, Watermeyer, …& Parra 2024) demonstrated in a small number (n=37) of healthy older adults that data collected using a web‐based, self‐administrated version of the task provides data comparable to that collected in laboratory conditions. Here we incorporated a machine learning (ML) approach to explore impacts of risk factors on this task in a larger digital dataset.

Method

Using data (n=359) collected from an online study incorporating the VSTMBT and lifestyle, psychological, and health data, we created a Binding Cost score which has shown to approximate AD‐related neuropathology (Parra et al., 2024). This categorised participants as either strong‐binders (SB – indicative of no pathology; 85.9% percent of the sample) or weak‐binders (WB – indicative of pathology; 14.1%).

We trained three ML algorithms (Random Forest (RF), K‐Nearest Neighbour (KNN) and Decision Tree (DT) by employing SMOTE technique to overcome the imbalance in group distribution. We applied a 10‐fold cross‐validation with hyper‐parameter tuning to optimise the models based on the selected variables (including age, sex, education, BMI, loneliness, and existing‐morbidities) to predict individual’s risk of cognitive impairment based on the groupings (SB vs WB). Models’ performances were examined on 20% of unseen test set.

Result

Aside from existing morbidities, which were higher in weak binders (WB = 0.41 (sd+2=0.79); SB =0.22(sd+2=0.49); t=2.21; p=0.03), other measures did not differ between groups. Regarding performance of the ML models, RF achieved the best performance (accuracy: 91%; recall=91%; precision=91%; AUC=97%) compared to KNN (accuracy: 81%; recall=81%; precision=84%; AUC=91%) and DT (accuracy: 81%; recall=81%; precision=82%; AUC= 85%). Feature importance analysis of the RF model suggests mental health, BMI, and fatigue have the highest impact on the prediction model, while sex and multi‐morbidity score have the least impact.

Conclusion

The study underscores the potential of web‐based cognitive assessments and ML for remote monitoring and early identification of AD risk factors, contributing to the advancement of accessible tools for early detection.
One‐week test‐retest reliability of an unsupervised, online version of the Digit Symbol Modalities task among older adults
Authors: Hooyman Andrew , Duff Kevin , Schaefer Sydney Y
Published: January 2025

Background

Measuring individual cognitive ability is critical for the diagnosis of neurodegenerative disease and prognosis of neurorehabilitation. Ideally, individual cognitive ability is achieved through an in‐person neuropsychological assessment by a trained and licensed clinician. However, there are several barriers that may prevent a prospective patient from being assessed (e.g., lack of transportation, reduced access to qualified professionals, etc.). Thus, we developed an online, unsupervised version of the digit symbol modalities task (DSMT), a subtest of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) that measures individual processing speed. The online DSMT can be performed both via a computer or touchscreen device. The purpose of this experiment was to examine the one‐week test‐retest reliability of the online DSMT among a group of adults 55 years and older.

Method

Sixty‐eight adults (mean age = 59.6 ± 4.8; female = 14, computer/touchscreen = 68/0) completed the initial and one‐week assessment of the online DSMT. Participants were presented with an instructional video on how to complete the assessment and a limited practice set of the DSMT to become familiarized. Presentation of symbol order was the same across each assessment day and between participants. A one‐way model of intraclass correlation for consistency was used to calculate the intraclass correlation coefficient (ICC).

Result

Results indicated an ICC = .68 (p<.001, 95% CI = [.52; .79]). Furthermore, a dependent t‐test between the initial test (mean = 29.2+/‐10.6) and the one‐week test (mean = 30.8+/‐11.5) was not statistically significant (p = .16), which indicates that performance was relatively stable between time‐points. This result is consistent with prior examinations of ‘good’ test‐retest reliability of the DSMT administered in‐person.

Conclusion

Overall, these results indicate that online, unsupervised DSMT performance is consistent across a one‐week period among adults 55 years and older. Furthermore, the transformation of what is commonly a paper‐and‐pencil test into an online assessment allows for the engineering of digital based performance features that may serve as potential digital biomarkers of neurodegeneration. Future research will validate online DSMT performance with other indicators of neurodegenerative disease.
Neuroimaging predictors of cognitive resilience in the presence of Alzheimer’s disease pathology
Authors: Williams McKenna E. , Fennema‐Notestine Christine , Bell Tyler R. , Lin Shu‐Ju , Glatt Stephen J. , Kremen William S. , Elman Jeremy A.
Published: January 2025

Background

Structural brain measures derived from magnetic resonance imaging (MRI) are commonly used to quantify Alzheimer’s disease (AD) progression, though their relationships with cognitive performance are highly heterogeneous. Some individuals demonstrate greater cognitive resilience—the ability to maintain cognitive performance despite adverse brain‐related changes—through as yet unknown mechanisms. We examined whether cortical thickness in specific regions confers resilience cross‐sectionally and/or longitudinally by moderating the relationships between established markers of AD risk and cognitive performance in amyloid‐positive adults.

Method

Amyloid‐positive participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) GO/2/3 cohorts with relevant imaging data were included (n=160, observations=473). Risk markers included a validated cortical thickness/hippocampal volume AD risk signature (weighted sum of cortical thickness from 7 regions plus hippocampal volume) and cerebrospinal fluid phosphorylated tau (p‐tau). Linear mixed effects models tested whether region‐specific cortical thickness moderated relationships between these markers of AD risk and memory or executive functioning.

Result

Cross‐sectionally, thicker cortex in a composite of 8 regions of interest (ROIs) minimized the negative impact of thinner cortex in AD risk signature regions on executive function performance. Higher thickness in a resilience composite of these 8 ROIs at baseline was associated with less decline in memory over time (p=0.007), independent of effects of other markers of AD risk. Moreover, higher baseline resilience composite scores weakened the negative longitudinal effects of p‐tau (p=0.014), independent of the longitudinal effects of AD risk signatures and age.

Conclusion

We identified 8 cortical regions that appear to confer cognitive resilience cross‐sectionally and longitudinally in the face of established indicators of AD pathology. Among amyloid‐positive individuals, thicker cortex in these resilience regions was cross‐sectionally associated with better executive function despite thinner cortex across established AD risk signature regions. Despite any cross‐sectional association with memory, thicker cortex in resilience regions predicted slower decline in memory over time and weakened the negative effects of p‐tau on memory over time. Preserved executive functioning associated with cortical thickness in these resilience ROIs may enable compensation in subsequent memory performance over time. These findings provide insight into possible mechanisms of cognitive resilience and individual variability in cognitive trajectories associated with AD.
Neuroinflammation potentiates the effect of amyloid‐β on longitudinal tau changes
Authors: Rahmouni Nesrine , Wang Yi‐Ting , Therriault Joseph , Servaes Stijn , Tissot Cécile , Macedo Arthur C. , Arias Jaime Fernandez , Hosseini Seyyed Ali , Stevenson Jenna , Kunach Peter , Hall Brandon J , Trudel Lydia , Gauthier Serge , Jeromin Andreas , Zetterberg Henrik , Blennow Kaj , Zimmer Eduardo R. , Ashton Nicholas J. , Benedet Andrea L. , Pascoal Tharick Ali , Rosa‐Neto Pedro
Published: January 2025

Background

It has been proposed that microglia release of proinflammatory factors reactive to amyloid plaques constitutes an early event leading to tau pathology. Here, we assessed how the rate of progression of tau‐PET and the rate of change in plasma pTau217 are affected by baseline levels of amyloid‐β and neuroinflammation.

Methods

We included 93 individuals from TRIAD cohort: 11 young individuals, 57 cognitively unimpaired elderlies, 15 with mild cognitive impairment and 10 individuals with Alzheimer’s Disease. Neuroinflammation, tau tangle and amyloid‐β (Aβ) deposition were assessed via [11C]PBR28‐PET, [18F]MK6240‐PET and [18F]AZD4694‐PET, respectively. Individuals also had plasma pTau217 quantified using the Alzpath assay. [11C]PBR28‐PET positivity was defined as a SUVR of 2.5SD above the mean of the young individuals in the precuneus and posterior cingulate. Voxel‐based regression models evaluated the interaction of TSPO‐ and Aβ‐PET with annual change in tau‐PET and plasma pTau217. The effect of the interaction on tau‐PET was also evaluated at the region‐of‐interest level using Braak regions. All models were corrected for age, sex and RFT corrected. Comparison of models was made using the Akaike Information Criterion (AIC) and the models’ goodness‐of‐fit was evaluated using R2 analyses. Models used [18F]MK6240‐PET SUVR yearly change as the outcome and used as predictors [11C]PBR28‐PET SUVR in the precuneus and posterior cingulate and [18F]AZD4694‐PET SUVR in the neocortical region.

Results

Positive associations were found between the interaction of Aβ‐ and TSPO‐PET at baseline predicting the yearly change in tau‐PET (Figure 1A). At the ROI level, the interaction significantly predicts tau load in Braak regions III‐IV in [11C]PBR28 positive individuals (Figure 1B). Positive associations were also found between the interaction of Aβ‐ and TSPO‐PET at baseline predicting the yearly change in plasma pTau217 (Figure 2A), which is driven by [11C]PBR28 positive individuals (Figure 2B). In addition, the interaction between Aβ‐ and TSPO‐PET predicting the yearly change in tau‐PET is the model with the highest R2 and the lowest AIC values in Braak regions III‐IV‐V‐VI (Figure 3).

Conclusion

These results support the hypothesis that microglial activation potentiates the effect of Aβ plaques on tau tangle progression and the pTau217 increases across the aging and AD spectrum.
Phase 2 Study Results of Oral ALZ‐801 (Valiltramiprosate) in Early Alzheimer’s Disease Shows Potential Disease Modification Effect: 2‐Year Effect on Plasma Biomarkers, Volumetric MRI, Cognition Outcomes and Clinical Benefit Analysis
Authors: Hey John A. , Abushakra Susan , Blennow Kaj , Kesslak Patrick , Hort Jakub , Prins Niels D. , Sheardova Katerina , Schaefer Jean , Albayrak Adem , Pak Winnie , Power Aidan , Tolar Martin
Published: January 2025

Background

ALZ‐801 (valiltramiprosate), an oral brain‐penetrant amyloid‐oligomer inhibitor in Phase 3 testing in APOE4/4 homozygotes (APOLLOE4 trial). A 2‐year Phase 2 biomarker study was completed evaluating ALZ‐801 (265 mg BID) on plasma biomarkers, MRI, cognition, and clinical benefit in EAD APOE4 carriers. At trial end, subjects could enroll in a 1‐year long‐term extension with an ongoing biomarker and cognition analysis.

Method

This 104‐week, open‐label study enrolled 84 subjects (MMSE 22‐30, CDR‐G 0.5‐1, positive amyloid‐PET or CSF biomarkers). Plasma and clinical testing occurred every 13 weeks; MRI every 52 weeks. Primary outcome was plasma p‐tau181; cognitive tests were Rey Auditory‐Verbal‐Learning Test (RAVLT) and Digit‐Symbol‐Substitution Test (DSST). Dr. Blennow’s Laboratory (Sweden) conducted plasma biomarker analyses (Simoa, Euroimmun assays). Hippocampal volume and cognitive tests were compared to matched group from ADNI‐1 observational study using simple matching (age, APOE4 genotype, disease stage) and propensity scores as covariates in the MMRM analysis. Clinical and HV benefit was determined by Cohen’s d score. For plasma biomarkers, observed data changes‐from‐baseline were analyzed with 2‐sided simple t‐tests.

Result

84 subjects were enrolled; 51% female, 69 years, MMSE 26.0, 70%/30% had MCI/Mild AD; 70 completed 104‐weeks. Plasma p‐tau181 showed significant reductions at all timepoints reaching 31%‐43% over 52‐104 weeks (p = 0.045); Aβ42 decreased ∼4% over 104 weeks (p = 0.042). Hippocampal atrophy (3.6%) was ∼28% lower than matched external control (ADNI‐1). RAVLT‐total memory and DSST remained above/at baseline through 104 weeks; Cohen’s d clinical benefit effect in RAVLT and hippocampal volume ranged from 0.5 to 0.7. Cognitive stabilization correlated with decreased hippocampal atrophy (Spearman’s r = 0.38‐0.43, p≤0.002); and cortical thinning (r = 0.35‐0.58, p≤0.004). Most common TEAE was mild nausea, and no ARIA‐E was observed.

Conclusion

Over 2 years, oral ALZ‐801 reduced plasma p‐tau181. Cognitive stabilization correlated with reduced brain atrophy, showing treatment benefit compared to external controls. Cohen’s d values for hippocampal volume and cognition suggest strong clinical benefit. No ARIA‐E/vasogenic edema was detected. These biomarker results support the disease‐modifying effects of ALZ‐801 in Early AD with promising clinical efficacy and favorable safety in APOE4 carriers. A Phase 3 78‐week trial in APOE4/4 homozygotes Early AD (EAD) is ongoing with results expected in 2024.
Large‐Scale Analysis of the Plasma Proteome and Cognitive Correlates in Traumatic Encephalopathy Syndrome and Chronic Traumatic Encephalopathy
Authors: Saloner Rowan , Casaletto Kaitlin B. , VandeVrede Lawren , Abisambra Jose F. F , Smith Glenn E. , Spina Salvatore , Grinberg Lea T. , Seeley William W. , Miller Bruce L. , Kramer Joel H. , Rabinovici Gil D. , Asken Breton M.
Published: January 2025

Background

Chronic traumatic encephalopathy (CTE) is a neurodegenerative tauopathy specific to individuals with repetitive head trauma. Traumatic encephalopathy syndrome (TES) is the proposed clinical syndrome resulting from CTE with or without other contributing neuropathologies. Pathophysiological mechanisms driving CTE and underlying TES symptoms are not understood. Using network‐based bioinformatics, we conducted the first large‐scale analysis of the plasma proteome in TES and CTE.

Methods

We leveraged a proximity extension assay (Olink Explore) to quantify 2,778 plasma proteins in 34 TES, 39 biomarker‐confirmed Alzheimer’s disease (AD), and 44 controls (HC; Table 1). TES was subdivided on Aβ‐PET status (23 TESAβ‐, 11 TESAβ+). Secondary analyses focused on antemortem plasma ofrom brain donors with autopsy‐confirmed CTE (N=8) and without (N=12). Differential abundance and network analyses of proteomic signatures were annotated via gene ontology and cell type enrichment. Protein co‐expression modules were age‐ and sex‐adjusted, and compared between groups using analysis of variance (Tukey’s post‐hoc with Cohen’s d). Within TESAβ‐, differential Spearman’s correlations examined individual protein associations with cognitive composites (memory, executive function, language, visuospatial) and co‐expression modules were tested for overrepresentation of cognitive‐associated proteins using Fisher’s exact tests with false discovery rate (FDR) correction.

Results

Differential abundance analysis revealed a bias towards increased plasma protein abundance in TESAβ‐, with enrichment for mitochondrial proteins (e.g., MECR, TOMM20). Network analysis identified 9 protein co‐expression modules (M1‐M9), of which 5 were elevated in TESAβ‐, but not TESAβ+ or AD, compared to HC (M1‐cell division/mitochondrion, d=1.4; M2‐TNF signaling/cell adhesion, d=0.72; M4‐cell metabolism, d=0.90; M5‐chemokine, d=0.80; M8‐muscle, d=0.88; Figure 1). Metabolic and immune‐linked signals in TESAβ‐ were replicated when comparing autopsy‐confirmed CTE to plasma of brain donors without CTE or those living with AD and HC. Within TESAβ‐, M2‐TNF signaling was highly enriched for proteins negatively associated with memory (FDR‐p=8.5e‐08) and executive function (FDR‐p=2.3e‐6).

Conclusions

Network‐based proteomics identified elevated peripheral molecular signatures that differentiated TES and autopsy‐confirmed CTE from healthy older adults and biomarker‐confirmed AD. Mitochondrial and inflammatory pathway dysregulation may be uniquely upregulated in CTE and underly cognitive changes in TES. Future protein‐specific assessment (Figure 2) will inform biomarker and therapeutic targets in older adults at greatest risk for CTE.