bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating the brain renin‐angiotensin system (RAS) and sex differences in pre‐clinical models of Alzheimer’s Disease
Authors: Paronett Elizabeth , Smith Hannah , Yu Zhe , Iyer Laxmi , Dunn Amy R , Kaczorowski Catherine C. , Marvar Paul
Published: June 2023

Background

Hypertension is linked to Alzheimer’s Disease (AD) risk, although the mechanisms remain unclear. The renin angiotensin system (RAS), critical for blood pressure homeostasis, is thought to contribute to AD pathology, and targeted RAS therapies are under current clinical investigation. To further evaluate the neurobiological mechanisms of RAS in AD, the current study leveraged two transgenic AD mouse models to compare the behavioral and cognitive deficits and the brain RAS in male and female mice.

Methods

A triple‐transgenic mouse model of AD (3xTg‐AD), which exhibits both amyloid beta and tau pathology, was used for in‐house assays, while an RNA‐sequencing database using a novel mouse model on a genetically diverse background (AD‐BXD) (GEO accession number GSE119215) was used to compare expression levels of hippocampal RAS genes at 6 and 14 mos. Morris water maze (MWM) and Y‐maze alternation tests were performed at early (3‐4 mos) and middle (5‐6 mos) time points on 3xTg‐AD mice (n = 8/sex/age/genotype), followed by collection of plasma and whole brain.

Results

Compared to controls, beginning at 3.5 months, 3xTg‐AD male and female mice exhibited deficits in learning assessed by MWM escape latency (p<0.01). However, beginning at 6 months, only 3xTg‐AD females had deficits in memory assessed by Y‐maze alternation below 50% (i.e. chance) (p<0.05). Sex‐dependent deficits are consistent with variability in phenotype beginning at early time points. Next we assessed hippocampal RNA‐sequencing data from the AD‐BXD database. These data demonstrated a sex‐dependent increase in expression of counter‐regulatory RAS genes ACE (p<0.0001) and ACE2 (p<0.05) and decrease in MasR (p<0.01) when comparing 6 and 14 month females, as compared to males and wild‐type controls. There was no change in classical RAS gene expression, indicating that variation in expression of neuroprotective but not classical RAS genes may be more pronounced in aging female mice.

Conclusion

Our results demonstrate sex and stage‐specific behavioral deficits in the 3xTg‐AD model, which may be linked to changes in hippocampal regulation of the counter‐regulatory arm of brain RAS. Additional studies are needed to further evaluate underlying mechanisms for the role of the neuroprotective arm of the brain RAS in AD and its biomarker and therapeutic targeting potential.
The association between Alzheimer’s disease blood‐based biomarkers and cognitive impairment and probable dementia in Look AHEAD MIND
Authors: Hayden Kathleen M. , Evans Joni K , Culkin Margaret C. , Molina‐Henry Doris P , Marcovina Santica , Shappell Heather M , Rapp Stephen R. , Sachs Bonnie C. , Ding Jingzhong , Mielke Michelle M. , Luchsinger Jose A , Espeland Mark A.
Published: June 2023

Background

The effect of an intensive lifestyle intervention (ILI) on Alzheimer’s disease (AD) blood‐based biomarker levels and cognitive outcomes among individuals with type 2 diabetes (T2D) is unknown. We examined AD biomarkers and cognitive outcomes in the Look AHEAD Study.

Method

Participants aged 45‐76 years were randomized at baseline to a 10‐year ILI or a diabetes support and education (DSE) condition. Cognitive assessments at years 8‐18 included measures of attention, executive function, global function, and memory. Mild cognitive impairment (MCI) and probable dementia were adjudicated by an expert panel. Stored baseline and end‐of‐intervention plasma samples were analyzed with the Quanterix Simoa HD‐X Analyzer. Changes in Aβ42/Aβ40, ptau181, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were evaluated in relation to randomization status, demographic characteristics, and cognitive outcomes. Cognitive scores and biomarker levels were converted to z‐scores. Cognitive trajectories were evaluated using mixed models to account for repeated measures; logistic regression was used for a composite outcome of MCI/dementia. Models were adjusted for baseline characteristics (age, sex, education, race/ethnicity, body mass index (BMI), CVD history, hypertension, diabetes duration, eGFR), APOE‐ε4, randomization arm, time from randomization, and time between blood draw and cognitive testing.

Result

The mean age of 779 participants was 61.4 years; 56% = female, 22.8% = APOE ε4+, mean BMI = 34.8, baseline diabetes duration >5 years = 57%, 16.7% Black, 12.5% Hispanic, 66.2% White, and 4.7% other racial and ethnic groups. There were no associations between the intervention and biomarker levels at baseline or biomarker change over time. Increases in NfL levels significantly predicted lower memory (‐0.04 ±0.01; p = 0.002), global cognition scores (‐0.05 ±0.02; p = 0.011), executive function (‐0.04 ±0.01; p = 0.01), as well as increased risk of MCI/probable dementia (odds ratio [OR] 1.10, 95% CI 1.02‐1.19). Increases in GFAP predicted lower memory (‐0.10 ±0.03; p = 0.0001), global cognition (‐0.09 ±0.03; p = 0.009), executive function scores (‐0.12 ±0.03; p<0.0001), and increased risk of MCI/probable dementia (OR 1.24, 95% CI 1.09‐1.41).

Conclusion

There was no association between the intervention and changes in biomarker levels. Increasing levels of NfL and GFAP over the ∼10 year period were associated with reduced cognitive performance and increased risk of MCI/probable dementia.
MRI signatures of Brain Age in the Alzheimer’s disease continuum
Authors: Shah Jay , Ghisays Valentina , Chen Yinghua , Luo Ji , Li Baoxin , Reiman Eric M. , Chen Kewei , Wu Teresa , Su Yi
Published: June 2023

Background

Age is the biggest risk factor for Alzheimer’s disease (AD). Substantial efforts to extract age signatures from magnetic resonance imaging (MRI) of the brain have achieved impressive accuracy and demonstrated these signatures were altered by neurological disorders including AD. In this work, we develop a deep learning model to characterize brain age signatures and examine their variation over the AD continuum.

Method

A 3D deep ResNet model was implemented to learn the structural signatures of brain age in predicting the chronological age of the participants. The model was trained on 7372 T1‐weighted MRI scans from a combined lifespan cohort of 5848 cognitively normal participants (age: 8‐ 95 yrs) using a 10‐fold cross validation procedure. The model was then applied to the independent ADNI cohort (N = 1175, 50‐98 yrs) to examine MRI derived brain age signatures variation in the AD continuum. The difference (∆age) between model predicted age and chronological age was used as the independent variable for group comparison using univariate ANCOVA tests, controlling for sex, education, and APOE4 gene dose, among five clinical groups: normal control (NC), normal to MCI converters (NC‐MCI), stable MCI (MCIs), MCI to AD converters (MCI‐AD), and AD patients.

Result

The ResNet model achieved an MAE = 3.76 yrs and R2 = 0.93 across 10 folds in the lifespan cohort. In the baseline data of the ADNI cohort, model derived ∆age increased along the AD continuum as expected: NC (‐1.2yrs) < NC‐MCI (‐0.7yrs) < MCIs (‐0.3yrs) < MCI‐AD (0.7yrs) <AD (1.5yrs) (F = 11.24, p<0.0001). Post‐hoc pairwise comparison results are summarized in Table 1/Figure 2. Although the difference between NC and NC‐MCI did not reach significance (p = 0.24) for the baseline data, comparison between the two groups using data from all visits was significant (p = 0.0009), suggesting more subtle differences.

Conclusion

A ResNet model was developed that captures the MRI signatures of brain age with high accuracy in age prediction. The model detected group level differences along the AD continuum in the expected direction. Subtle changes in brain signatures were observable in normal participants who later developed cognitive impairment. Our technique provides a novel approach to investigate the relationship between aging and AD.
Correlation between depression, loneliness, challenging behavior and MRI findings among persons with high‐risk for cognitive impairment (PWHRCIs)
Authors: Chiu Yi‐Chen , Yeh Chun‐Hung , Jou Shing‐Yi , Hsiao Ing‐Tsung , Toh Cheng‐Hong , Chao Yi‐Ping , Hsu Wen‐Chuin
Published: June 2023

Background

this study explored the relationships between depression, loneliness, challenging behaviors among persons with high‐risk for cognitive impairment (PWHRCIs). MRI findings were collected as well.

Method

This was a secondary analysis of a cross‐sectional study. Primary data were collected from the mother project “ Social Cognition, Nutrition and Cognitive Function in Middle Life: A Longitudinal Study ” (MOST‐107‐2314‐B‐182076) between 2018 to 08/14/2021. 176 participants were recruited, among which 24 participants had received MRI examination. Test battery included: Taiwanese version of Frontal Behavioral Inventory (TFBI) for challenging behaviors, the Geriatric Depression Scale Short Form (GDS‐SF) for depressive symptoms, the short‐form UCLA Loneliness scale (ULS‐8) for loneliness, the Mini‐Mental State Examination (MMSE) for global cognition, while MRI indicators included T1‐weighted image (T1W1), Resting‐state functional MRI (RS‐fMRI) and Diffusion Weighted Image (DWI).

Result

hierarchical regression model results show: Model I, depressive symptoms predicted challenging behavior, explaining 12% of variance (R2 = .12). Model II, loneliness was added and significantly predicted challenging behavior with an 8% of increased variance. In total, Model II explained 20% of variance. Therefore, loneliness is a mediator between depressive symptoms and challenging behavior. 2. Loneliness was significantly correlated with the Brain Structural Networks (normalized characteristic path length) (r = ‐.47*, p<.05). 3. Challenging behavior was significantly correlated with the Brain Structural Networks (normalized characteristic clustering coefficient and normalized characteristic path length) (r = .78, p<.01; r = .83, p<.01, respectively). 4. Challenging behavior was significantly correlated with the Brain Functional Networks (Small‐world index and normalized characteristic clustering coefficient) (r = ‐.57, p<.05; r = ‐.49, p<.05, respectively), while the network indicator was thought to be random.

Conclusion

The results indicated that depression and loneliness an affect challenging behavior in PWHRCIs. The results of MRI findings also highlight the importance of loneliness which may slow down the structural connections in the brain to transmit messages. Challenging behavior is also associated with functional brain connectivity. Therefore, it is necessary to regularly assess the emotional factors of PWHRCIs and provide individualized care to avoid further damage to their brain.
FNDC5/irisin expression stimulates neuroprotective pathways in hippocampal neurons and associates with Alzheimer’s disease pathology
Authors: Raony Ícaro , de Freitas Guilherme B. , Ferreira Sergio T. , Lourenco Mychael V. , De Felice Fernanda G.
Published: June 2023

Background

Irisin is an exercise‐linked myokine produced by cleavage of the membrane precursor fibronectin type III domain‐containing protein 5 (FNDC5) in skeletal muscle, brain, and other tissues. Recently, irisin has been identified as a key molecule for exercise‐induced neuroprotection in mouse models of Alzheimer’s disease (AD). However, the role of FNDC5/irisin in AD pathology has not yet been comprehensively explored. Here, we investigated potential mechanisms underlying neuroprotection induced by FNDC5/irisin in AD.

Method

Primary rat hippocampal neuronal cultures were transduced with adenoviral vectors to express FNDC5 (AdFNDC5) or GFP (as a control) or exposed to recombinant irisin (25 nM) for defined timepoints. Brain‐derived neurotrophic factor (BDNF) levels were measured by ELISA; extracellular signal‐regulated kinase 1/2 (ERK 1/2) phosphorylation was determined by Western blotting; and the effects of irisin on amyloid‐β oligomers (AβO)‐induced reactive oxygen species (ROS) accumulation was determined by the DCF fluorescence. Finally, we analyzed RNA‐seq data from human postmortem hippocampi within The Aging, Dementia and Traumatic Brain Injury Study to determine potential correlations between FNDC5 gene expression and AD pathology.

Result

We found that irisin stimulates extracellular BDNF accumulation, ERK 1/2 phosphorylation (i.e. activation) and prevents AβOs‐induced ROS accumulation in primary hippocampal neurons. Analysis of RNA‐seq data indicates that hippocampal FNDC5 gene expression is reduced with aging and tau (assessed by Braak neuropathological scale and hippocampal phospho‐tau immunoreactivity), but not with amyloid pathology in humans.

Conclusion

These results indicate potential mechanisms by which FNDC5/irisin signaling promotes neuroprotection and support the notion that stimulation of irisin signaling may be beneficial against neurodegeneration in AD.
Impacts of cerebral small vessel disease on global and domain‐specific cognition
Authors: Ariko Taylor , Gardener Hannah , Levin Bonnie , Sun Xiaoyan , Merritt Stacy S , Zhao Weizhao , Mora‐McLaughlin Consuelo , Gutierrez Jose , Elkind Mitchell S.V. , Sacco Ralph , Alperin Noam , Rundek Tatjana
Published: June 2023

Background

The 2021 Alzheimer’s Association International Conference press release forecasted global dementia cases to triple by 2050, due to the major contribution of increases in vascular risk factors. The Global Vascular Risk Score (GVRS) was developed to predict vascular events using a point‐based index for risk factor variables, though has demonstrated to be a significant predictor of global and domain‐specific cognitive performance in a multi‐ethnic cohort (Rundek, T. et al. Global Vascular Risk Score and CAIDE Dementia Risk Score Predict Cognitive Function in the Northern Manhattan Study. J Alzheimers Dis 73, 1221‐1231 (2020)). However, more than half of the variance in global and domain‐specific cognitive performance is still unexplained by GVRS variables. We sought to explain additional variance in cognitive performance by addition of MRI biomarkers of cerebral small vessel disease to the GVRS model.

Method

We included 1290 subjects from the multiethnic Northern Manhattan Study population (age 64+/‐8 years, 40% women, 66% Hispanic, 17% non‐Hispanic Black, 15% non‐Hispanic White, education 10+/‐5 years). Multivariate linear regression models were employed to assess the added value of the cerebral small vessel disease MRI measures (white matter hyperintensity volume, silent brain infarcts, cerebral microbleeds, and perivascular spaces) beyond GVRS variables in explaining more variance in global and domain‐specific (episodic memory, executive function, semantic memory, and processing speed) cognitive performance. The explained variance (R2) of the GVRS model was compared to the proposed model with added imaging markers to determine their predictive performance. Statistical significance was determined using F‐statistic difference test between the models.

Result

The explained variance (R2) and F‐statistic for models of global and domain‐specific cognition are in the table. Addition of MRI measures significantly improved the model for global cognition (F(4, 1108) = 2.68, p < 0.05) and domain‐specific cognitive performance models of episodic memory (F(4, 1096) = 3.34, p < 0.01) and processing speed (F(4, 1096) = 2.40, p < 0.05).

Conclusion

MRI measures of cerebral small vessel disease explain more variance in global cognition, episodic memory, and processing speed than GVRS factors alone. However, most of the variance in cognitive performance remains unexplained.
Reduced cortical cholinergic innervation correlates with cognitive decline in mild cognitive impairment
Authors: Xia Ying , Eeles Eamonn , Fripp Jurgen , Pinsker Donna , Thomas Paul , Latter Melissa , Dore Vincent , Fazlollahi Amir , Bourgeat Pierrick , Villemagne Victor L , Coulson Elizabeth J , Rose Stephen
Published: June 2023

Background

Dysfunction of the cholinergic basal forebrain (BF) neurotransmitter system, including cholinergic axon denervation of the cortex, plays an important role in cognitive decline and dementia. The association of cortical cholinergic denervation with diverse cognitive profiles in dementia, particularly at early stages, has not yet been fully explored. We assessed the relationship of cholinergic denervation in the cortex measured using 18F‐fluoroethoxybenzovesamicol (FEOBV) with cognitive decline at an early stage of dementia.

Method

Participants (8 with mild cognitive impairment (MCI) and 10 cognitively unimpaired (CU) controls, aged 60‐86, 55.6% female, MMSE = 28.7±1.5) underwent neuropsychological assessment and FEOBV PET imaging. The neuropsychological battery of tests included measures of memory, executive function, attention and language. Domain‐specific composite scores were calculated by averaging z‐scores of the related tests or subtasks within a domain. FEOBV images were co‐registered to the concurrent structural MRI and normalised to the supratentorial white matter reference region resulting in a standardized uptake value ratio (SUVR). Voxel‐wise analysis was performed on normalised FEOBV images to investigate associations with clinical diagnosis and domain‐specific cognitive performance. Voxel‐based morphometry was also performed to rule out differences in brain morphology. All analyses were corrected for age, sex and total intracranial volume and adjusted for multiple comparisons.

Result

The MCI group showed significantly lower global FEOBV SUVR in the cortex although only a focal cluster of reductions near the right middle temporal gyrus was found in the voxel‐wise comparisons. When associations with cognitive performance profiles were assessed in the full cohort, regional positive correlations were found between FEOBV SUVR and cognitive scores across different domains (Figure 1), although these did not include memory. For executive functioning, widespread correlation patterns were observed across both cortical and subcortical regions. Moreover, overlapping profiles were identified for all three cognitive domains of executive function, attention and language, which covered the anterior cingulate gyrus, olfactory cortex, calcarine cortex, middle temporal gyrus and caudate nucleus.

Conclusion

We have demonstrated that the topographic profile of FEOBV retention correlated with reduced cognitive performance in different domains, suggesting that reduced cortical cholinergic terminal integrity is an important pathological feature of cognitive decline.
Identifying network hubs from brain anatomical similarity networks
Authors: Mastrou Andreas , Vuksanovic Vesna
Published: June 2023

Background

Brain hubs are highly connected regions important for integrating cognitive processing in the healthy brain. Brain hubs also play role in neurodegeneration causing dementia. However, it is not clear what brain morphometry is most useful in identifying brain regions critical to their involvement in neurodegeneration.

Method

We examined brain network hubs from four measures of cortical morphometry, derived using anatomical T1‐weigher MRI. From a large cohort of healthy participants (N = 260) from 20 to 85 years of age, we generated 200 networks for each measure of cortical morphometry using bootstrapping. We then tested how two measures of brain network hubness – nodal strength and clustering coefficient – were mapped onto brain network hubs across all 200 networks for each morphometric feature. Regions were identified as brain hubs if ranked two standard deviations away from the corresponding group mean.

Result

We mapped out brain hubs for each four measures (features) of brain morphometry. Nodal strength and clustering coefficient showed similarity in the behaviour across the features: gray volume, regional surface area and its thickness and thickness standard deviation. However, the differences were found in what brain region qualify as a network hub for each feature.

Conclusion

Cortical morphometry extracted from anatomical brain scans can be used as a potential imaging marker for identification of brain hubs potentially involved in early differentiation of dementia subtypes.

References: Vuksanović V, Staff RT, Ahearn T, Murray AD, Wischik CM. Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer’s Disease and Behavioral Variant Fronto‐Temporal Dementia. Int J Neural Syst. 2019 Aug;29(6):1850055. https://doi.org/10.1142/S0129065718500557.

Evans AC. Networks of anatomical covariance. Neuroimage. 2013 Oct 15;80:489‐504. https://doi.org/10.1016/j.neuroimage.2013.05.054.
Association of the frailty index with functional brain connectivity in the Irish Longitudinal Study on Ageing (TILDA)
Authors: Davis James , Zuniga Raquel Gutierrez , Boyle Rory , Looze Celine De , Meany James F , O’Halloran Aisling M , Whelan Robert , Kenny Rose Anne , Ortuño Roman Romero , Knight Silvin P
Published: June 2023

Background

Frailty, expressed as accumulation of health deficits in older adults, could contribute to the risk of cognitive decline. We cross‐sectionally studied the brain connectivity signatures of frailty in The Irish Longitudinal Study on Ageing (TILDA).

Method

We included participants from Wave 3 of TILDA who underwent resting‐state functional MRI. Connectivity maps were based on Shen’s parcellation and connectome‐based predictive modeling was used to find associations between connectivity and frailty as measured by Frailty Index (FI) (Table 1).

On each iteration of a 10‐fold cross‐validation the training folds were utilized to perform partial Spearman correlations (adjusted for age, sex, and mean framewise displacement) between each brain connection and FI scores. Connections with p<0.001 correlations were selected. Network strength was computed by summing the correlations across all connections selected and a linear model built using the network strength to predict FI score. After 10 folds are complete the performance was measured with linear R values between predicted and true FI scores. This process was repeated 1000 times (with random cross‐validation splits) and mean performance metrics obtained. A permutation test was employed in which the above procedure was repeated 1000 times, with FI scores shuffled each time. Significance of selected connections was calculated as the number of permutations scores that were equal to or greater than the proper mean score, divided by 1000.

Result

347 participants were included (mean age 67.7 (SD 7.3) and 51.6% men). We obtained a connectivity network that positively correlated with frailty (“frailty network”) (R = 0.169, p = 0.006) and another that negatively correlated with frailty (“robustness network”) (R = ‐0.193, p = 0.006); and are depicted in Figure 1. The “frailty network” was more widespread and showed higher connectivity from right occipital to both prefrontal cortices, subcortical and left temporal cortex, whereas the “robustness network” exhibited higher functional connectivity in subcortical to left parietal and bilateral temporal cortices.

Conclusion

Functional brain connectivity could be influenced by frailty. Further research should study the relationship of brain connectivity and different tools for frailty and establish how different patterns of deficit accumulation affect brain health across lifespan.
Brain white matter and resting state eeg markers are abnormal in HIV subjects with relatively good cognitive status
Authors: Noce Giuseppe , Percio Claudio Del , Piervincenzi Claudia , Carducci Filippo , Lizio Roberta , Onorati Paolo , Toma Ginevra , Ferracuti Stefano , Soricelli Andrea , Pennica Alfredo , D'Ettorre Gabriella , Petsas Nikolaos , Andreoni Massimo , Calcagno Andrea , Babiloni Claudio
Published: June 2023

Background

This retrospective and exploratory study tested the concept that at the group level, human immunodeficiency virus (HIV) can significantly affect brain structure and function before the manifestation of significant cognitive deficits.

Method

From a multicenter database, we selected structural 3T magnetic resonance imaging (MRI) and resting state eyes‐closed electroencephalographic (rsEEG) datasets in 30 HIV‐positive (HIV) subjects with relatively good cognitive status and serological markers (i.e., HIV‐RNA copies and CD4 count). Control datasets of matched non‐infected subjects included rsEEG (N = 50) and MRI (N = 30) recordings. MRI markers of interest in HIV were derived from gray matter (GM) volume decrements and white matter (WM) lesion load, while rsEEG markers were cortical source current density estimated by LORETA freeware at relevant delta (< 4 Hz) and alpha (6‐12 Hz) individual frequency bands.

Result

In the HIV group, the subjects exhibited no abnormal score in neuropsychological tests. However, those subjects showed brain GM volume and WM abnormalities correlated with serum CD4 count (Figure 1). They also showed diffuse abnormalities in rsEEG alpha source activities.

Conclusion

At the group level, HIV subjects with relatively good cognitive status can show abnormalities in both structural MRI and rsEEG markers. If cross‐validated in longitudinal studies, combined MRI and rsEEG markers may be a useful surrogate endpoint to test antiretroviral therapies with putative neuroprotective function.
Genomewide analysis of Episodic Memory trajectories in The Mexican Health and Aging Study (MHAS)
Authors: Chen Lixian , Arango Silvia Mejia , Obregon Alejandra Michaels , Samper‐Ternent Rafael , Wong Rebeca , Reyes‐Dumeyer Dolly , Renteria Miguel Arce , Tosto Giuseppe , Barral Sandra
Published: June 2023

Background

Genetic characterization of age‐related memory changes can help identify population subgroups at‐risk of memory decline and dementia. The majority of genetic studies examining memory trajectories in old age have used data from non‐Hispanic White populations. To our knowledge, there are no reports of genetic factors underlying memory function over time in the Mexican population.

Method

Using a previously described latent curve model approach, we estimated episodic memory trajectories in a longitudinal sample from the Mexican Health and Aging Study. We conducted GWAS analyses in a sub‐sample of 6,343 participants. Analyses were stratified by memory stability (Stables, n = 4,437) and APOE status. Three independent cohorts were used for replication purposes: two Non‐Hispanic White samples from the Alzheimer’s Disease Genetic Consortium and the Religious Orders Study, and a Caribbean‐Hispanic sample from the Washington Heights Inwood Community Aging Project.

Result

The strongest genome‐wide significant association was found for an intronic variant in the NR2F1‐AS1 gene (rs555528825, p = 1.8×10−9) among APOE non‐E4 carriers in the “Stables” group. NR2F1 gene is an evolutionarily conserved long non‐coding RNA that enhances neuronal cell maturation and regulates transcription of neuronal genes. SNP variants located less than 50Kb apart from the identified signal showed also nominally significant associations in the three replication datasets (p = 3.9×10−4, p = 1.8×10−4, and p = 0.006 respectively). Additional replication efforts using the UK biobank recourse are ongoing.

Conclusion

Our study nominates novel genetic variants associated with longitudinal changes in episodic memory performance using data from the Mexican Health and Aging Study, a representative and comprehensive longitudinal study that includes genetic data on a sub‐sample of participants 50 years and older.
Explainable machine learning aggregates polygenic risk scores and electronic health records for Alzheimer’s disease prediction
Authors: Gao Xiaoyi Raymond , Chiariglione Marion P , Nuytemans Karen , Li Yi‐Ju , Martin Eden R.
Published: June 2023

Background

Alzheimer’s disease (AD) is the most common late‐onset neurodegenerative disease. Identifying individuals at increased risk of developing AD is important for early intervention. Risk prediction models are typically based on a limited number of predictors, possibly with sub‐optimal performance. Here, we explore an explainable machine learning (ML) framework, XGBoost and SHapley Additive exPlanations (SHAP) values, for AD risk prediction, which can handle a large number of predictors and output the impact and importance of each predictor.

Method

We developed an XGBoost model that aggregates polygenic risk scores (PRSs), which include both PRS for AD risk and PRS for age at onset of AD, baseline individual characteristics (e.g., non‐genetic factors), and information from electronic health records for predicting incident AD. The PRSs were derived using summary statistics from genome‐wide association studies in the Alzheimer’s Disease Genetics Consortium (ADGC) dataset (n = 19,918). The model was applied to 457,936 white participants in UK Biobank to predict development of AD within 10 years after the baseline visit (n = 2,177 developed AD). We further used SHAP values to explain the relative information in model predictors.

Result

For participants of age 40 and older, the area under the receiver operating characteristic curve (AUC) for AD risk prediction was over 0.880. PRSs ranked second to age (the best predictor) in feature importance. For subjects of age 65 and above, PRSs for AD were the most important features. Our ML model not only identified traditional risk factors for AD, such as age, education, income, body mass index, diabetes, and blood pressure, but also identified predictors from electronic health records that are not typically considered in traditional prediction models, including urinary tract infection, syncope and collapse, chest pain, disorientation and hypercholesterolaemia, for developing AD. Furthermore, SHAP values aided the ranking of feature importance and model explanation.

Conclusion

Our ML model improves the accuracy of AD risk prediction by efficiently exploring numerous predictors. PRSs play the most important role in developing AD in individuals of age 65 and older. In application, the model also identified novel feature patterns for AD.
An analysis of factors influencing dementia study enrollment: Focus groups with diverse community members viewing the ACTNOW research registry website
Authors: Tran Leslie , Nunnerley Michael , Gothard Sarah , Golonka Ona , Pierce Aimee , Lindauer Allison
Published: June 2023

Background

Many barriers discourage individuals from enrolling in dementia research studies, such as lack of information, web accessibility, and transportation. Research stakeholder feedback is necessary to understand these barriers. We used virtual focus groups to learn how to improve the website of our local research registry: ACTNOW (Alzheimer’s Comprehensive Treatment Network of Oregon and Washington). Local community members from diverse backgrounds interacted with the study team to provide insight on some of the roadblocks to research participation. Here, we report on findings from the focus groups and participants’ feedback related to the ACTNOW website and user engagement.

Method

Three 90‐minute virtual focus groups (fg) were conducted with 19 participants via videoconferencing. Inclusion criteria were ACTNOW members, African American, and low‐income and rural‐dwelling individuals combined respectively. Participants completed pre‐and post‐focus group surveys about their thoughts on the ACTNOW website and interest in dementia research. Investigators from the research team analyzed the survey data and independently coded the written transcripts from the group discussions using the Dedoose coding software.

Result

There were 19 participants overall (fg_1 = 8, fg_2 = 5, fg_3 = 6). The mean age was 66.9; 89.5% of the sample was female; and 57.9% were white. The analysis revealed that the participants had concerns about the readability of the website and the clarity of purpose of ACTNOW (e.g., “I look at this, and I say, whoa, wait a minute they want me to sign up for what?”). Most of the topics discussed suggested consumers did not understand the purpose of the website or ACTNOW’s promotional materials, resulting in a fear of signing up for the actual program (research registry). Survey data reported a large interest in dementia research but a need for more consumable, relevant information, such as explaining the benefits of research and requirements of being an ACTNOW member.

Conclusion

Findings demonstrate specific website usability challenges and reasons that prevent community members from signing up for dementia research. Understanding the focus group participants’ feedback is important in fostering greater diversity, appeal, and accessibility in dementia research.
High health coaching adherence increases Alzheimer’s protection in at‐risk inviduals following a 4‐month intervention
Authors: Campitelli Anthony , Paulson Sally , Gills Joshua L. , Jones Megan , Madero Erica N. , Myers Jennifer Rae , Glenn Jordan M. , Gray Michelle
Published: June 2023

Background

Alzheimer’s disease and related dementias (ADRD) imposed an estimated financial cost to Americans of $355 billion in 2021 and is projected to rise to $1.1 trillion by 2050. ADRD affects more than 6 million Americans and is expected to rise to more than 13 million by 2050. Health coaching (HC) interventions improve many lifestyle factors also known to be protective against ADRD; however, their ability to provide protection in individuals at‐risk for developing cognitive decline is unknown. The purpose of the present investigation was to examine the effect of HC intervention adherence on ADRD protective factor score after 4 months.

Method

Adults aged 45‐75 years (n = 104) with at least two ADRD risk factors and a maximum of one protective factor participated in this study. Participants completed the Australian National University Alzheimer’s Disease Risk Index (ANU‐ADRI) both before and after a 4‐month HC protocol focusing on reducing modifiable risk factors for ADRD in six domains (diet, exercise, sleep, stress, social engagement, and cognitive activity). Participants who completed a number of check‐ins with the health coach greater than the group mean (5.6 check‐ins) were placed in the high adherence (HA) group, and individuals with fewer were placed in the low adherence (LA) group. A mixed factorial ANOVA was conducted to determine if there was a difference in pre‐ and post‐ANU‐ADRI overall protective factor score.

Result

After the 4‐month HC intervention, ANU‐ADRI scores did not change overall in the pooled sample (F(1,102) = 1.45, p = .23). However, a significant adherence*time interaction effect indicated that HA improved overall protective factor score significantly more than LA (F(1,102) = 4.85, p = .03), and pairwise comparisons revealed that protective factor scores improved only in the HA group (p = .02 for HA versus p = .47 for LA).

Conclusion

These results indicate an HC intervention may effect behaviors and emotional states understood to be ADRD protective factors when adherence with the protocol is high. This has the potential to improve the quality of life for individuals at‐risk for ADRD. Further investigation will shed light on whether the ADRD protection derived from HC is iterative and durable.
Use of the human reference genome 38 enhances integration of the multi‐tissue proteomics with genetics and disease
Authors: Yi Heng , Yang Qijun , Timsina Jigyasha , Wang Fengxian , Wang Lihua , Cruchaga Carlos , Sung Yun Ju
Published: June 2023

Background

Most existing protein quantitative trait locus (pQTL) studies focus on a single tissue and use the reference Genome Reference Consortium Human Build 37 (GRCh37/hg19) published in 2009. GRCh38/hg38 was updated in 2013 with correcting thousands of sequencing artifacts that cause false SNPs and updating non‐nuclear genomic sequence. Many papers strongly recommend switching to GRCh38/hg38. The goal of this study is to use multiple tissues (brain, CSF and plasma) to explore the genetic architecture of protein levels in neurologically relevant tissues and to update the human reference genome as hg38 to compare the findings.

Method

In this study, 805 CSF samples and 869 proteins, 529 plasma samples and 953 proteins and 378 brain samples and 1,300 proteins passed quality control process. We performed genome‐wide association analyses of over 8 million autosomal variants (MAF ≥ 0.01) imputed using the most updated hg38 TOPMed imputation panel to identify cis/trans pQTLs. We performed conditional analysis to identify independent pQTLs. After removing pleiotropic loci and including Alzheimer’s disease (AD) variants, Mendelian randomization (MR) was applied to detect the casual associations between proteins and AD risk. To decrease unmeasured pleiotropy effect, we used co‐localization analysis to get more supporting information among multiple traits. Finally, we replicated our findings in much larger studies.

Result

In brain tissue, we identified 4269 pQTLs in hg38 compared to 2418 pQTLs in hg19 with a threshold of 5 × 10−8 for cis‐pQTLs and 5 × 10−8/(number of independent proteins) for trans‐pQTLs. We found the independent SNPs and highlight the complexity of regions with multiple independent local pQTLs. Analysis for CSF and plasma is underway.

Conclusion

This study is to apply the hg38 as the human reference genome to detect much more pQTLs and correct possible false findings in the previous hg19 study. With the following analysis, we could get more valuable and confirmed information about the additional GWAS loci and identify the function of certain proteins on the disease risk. The multiple tissue samples and multiple traits could help us detect the complex genetic architecture of protein levels in neurologically relevant tissues.
Pharmacologic inhibition of astrocyte ApoE release
Authors: Kulas Joshua A , Kovacs Michael A , Milstein Joshua L , Harris Taije H , Ferris Heather A
Published: June 2023

Background

The ApoE4 allele is the strongest known genetic risk factor for late onset Alzheimer’s disease. Despite this knowledge, therapeutic strategies seeking to modulate brain ApoE homeostasis remain largely unexplored. Several lines of evidence demonstrate that astrocytes function as the primary producers of ApoE within the brain. In this study, we examine how targeted disruption of astrocyte lipid metabolism and protein prenylation effect the secretion of ApoE from primary astrocyte cultures.

Method

Primary cell cultures of mouse astrocytes were grown from 1‐3 day old pups. Drugs were applied to cells in serum free conditions over a range of timepoints and doses. Astrocyte conditioned media was collected from cultures and ApoE and other proteins of interest were measured by western blot.

Result

We find that inhibiting HMG‐CoA reductase, a rate‐limiting enzyme in the cholesterol synthesis pathway, with simvastatin reduces astrocyte ApoE levels in conditioned media in a dose dependent manner, while secretion of other proteins remain preserved. Inhibition of downstream cholesterol synthesis through blockade of the enzyme FDFT1 with zaragozic acid, however, has no effect on total ApoE secretion. Mice with genetic disruption of brain cholesterol metabolism also have similar levels of ApoE in CSF samples compared to control. These data suggest the effect of HMGCR inhibition on ApoE is not mediated through cholesterol. It is known that HMGCR activity is also required for maintenance of cellular protein prenylation. We tested the prenylation inhibitor FGTI‐2734 and found that it is sufficient to block astrocyte ApoE secretion, suggesting that HMGCR inhibitors may exert their effect on ApoE through this mechanism. Recent work suggests that inflammatory astrocytes exert toxic effects via neurotoxic lipids carried by ApoE and another carrier protein, CLU. We find that inhibiting HMGCR in astrocytes does not prevent cytokine‐induced conversion to an inflammatory phenotype, but remains able to block ApoE release

Conclusion

We conclude that targeted inhibition of prenylation enzymes may provide a therapeutic strategy to modulate ApoE levels in the brain.
Heterogeneous effect of social and behavioral determinants of health on the risk of dementia
Authors: Tang Huilin , Wu Yonghui , Brown Joshua , Anton Stephen , Hernandez Inmaculada , Bian Jiang , Guo Jingchuan
Published: June 2023

Background

Individuals experiencing socioeconomic disadvantages are disproportionally affected by dementia. Social and behavioral determinants of health (SBDH) are major contributors to health inequities in dementia risk and outcomes. We aimed to determine the heterogeneous effect of SBDH on dementia risk in older adults.

Method

Using data from the National Alzheimer’s Coordinating Center (NACC) (2005‐2021), we identified adults 65 years and older with ≥2 visits and normal cognition at baseline. Exposures of interest included four SBDH collected at baseline, including alcohol abuse, drug abuse, smoking, and high school education or above. We applied a causal machine learning model and doubly robust learning to estimate the conditional average treatment effects (CATEs) and heterogenous effect of SBDH on the risk of dementia. Following the doubly robust learning framework, we created the models in a two‐step process: a first model that estimates the probability of being exposed (i.e., generating propensity scores), and then a second model that estimates dementia outcome from the exposures of interest, accounting for the probability of being exposed. Hyperparameter optimization and model validation were conducted based on minimal mean square error.

Results

We included 10,375 participants, with a mean age of 75 (SD: 7) years; 64% were women and 9% (n = 954) developed dementia over a median follow‐up of 5.2 years. In the estimation of CATEs, higher education was associated with a lower risk of dementia (absolute risk deference: ‐0.038; 95%CI, ‐0.065 to ‐0.01), while smoking (‐0.002; ‐0.009 to 0.005), alcohol abuse (‐0.073; ‐0.152 to 0.005), and drug abuse (‐0.024; ‐0.051 to 0.004) were not significantly associated with dementia risk. However, we identified a heterogeneous effect for each of these SBDH (Figure). Over 53%, 68%, and 28% of individuals had an increased risk of dementia with exposure to smoking, alcohol abuse, and drug abuse, respectively.

Conclusion

We identified significant heterogeneous effects of SBDH, specifically smoking, alcohol abuse, and drug use, on dementia risk in a group of older adults with normal cognition. Our findings underscore the need to adopt an individualized approach to address dementia disparities. Future studies should examine the mechanisms underlying the heterogenous effects of SBDH on dementia risk.
Dementia increases risk of organ failure and hospital mortality of motorcycle crash‐related hospitalizations in Taiwan: A nationwide population‐based study
Authors: Liu Chih‐Ching
Published: June 2023

Background

Prior studies showed dementia is associated with the increased risk of injuries in motorcycle crashes, especially in young onset dementia. However, little is known about the effect of young onset dementia on the risk of organ failure and hospital mortality of motorcycle crash‐related hospitalizations. This study describes the prevalence of organ failure and hospital mortality of motorcycle crash‐related hospitalizations among patients with and without dementia and assesses whether dementia is at higher risk of organ failure and hospital mortality of motorcycle crash‐related hospitalizations.

Method

In this population‐based cohort study, we compared patients with dementia aged 40‐64 years and its age‐ and sex‐ matched participants without dementia when they had the first hospitalization for motor vehicle accident injury (MVAI). Data in this study were obtained from the Taiwan National Health Insurance Research Database entries and Taiwan Police‐reported Traffic Accident Registry between 2006 and 2015. Major outcomes were development of organ failure and hospital mortality in motorcycle crash‐related hospitalizations. Logistic regression with generalized estimating equations were performed to account for hospital clustering effect.

Result

In patients with dementia, the prevalence rates of organ failure and hospital mortality was 6.88% and 4.44%, respectively, which were higher than participants without dementia (3.08% and 2.07%). After adjustment of potential confounders, patients with dementia had a 91% higher risk (95%CI 1.45‐2.51) of organ failure of motorcycle crash‐related hospitalizations than patients without dementia, especially those with respiratory organ failure (adjusted odds ratio [OR]1.96, 95%CI 1.46‐2.63). Similarity, patients with dementia were related with increased risk of hospital mortality (adjusted OR 1.39, 95%CI 1.01‐1.93).

Conclusion

In motorcycle crash‐related hospitalizations, the presence of dementia may rise the risk of organ failure and hospital mortality, which warrants the concerns of healthcare providers.
Sex differences of APOE neuropathology‐based scores in brain aging
Authors: Adluru Nagesh , Deming Yuetiva , Nair Veena A. , Prabhakaran Vivek , Bolaños Alfredo D , Lose Sarah R , Alexander Andrew L , Okonkwo Ozioma C. , Bendlin Barbara B
Published: June 2023

Background

By reinterpreting the difference between a model prediction and calendar age, machine learning algorithms allow for estimation of “brain age” using MRI. There is growing evidence for sex differences in the influence of APOE genotype (evaluated as APOE ε4 carrier status) on Alzheimer’s disease (AD) endophenotypes at various stages of disease. The purpose of this study is to examine the influence of an APOE neuropathology‐based score (APOE npscore) on the brain aging estimated from deep learning.

Methods

Brain age from 274 participants (Fig. 1) in the Wisconsin‐ADRC was estimated from T1w‐MRI using a publicly available deep learning model called two‐stage‐age‐network (TSAN) that was pre‐trained on over four thousand scans from OASIS, ADNI‐I and PAC‐2019. TSAN uses a novel rank‐based loss along with mean squared loss and makes predictions in two steps which does not require a posteriori bias correction. This is a significant improvement from prior deep learning models in reducing the “regression‐to‐mean bias” typically present in brain age models. APOE genotypes (ε2ε2, ε2ε3, ε3ε3, ε2ε4, ε3ε4, ε4ε4) were weighted by the log(odds‐ratio) from a large study of autopsy‐confirmed AD cases/controls, providing a variable representing the relative amount of risk across APOE genotypes. Mood’s median test was used to examine the sex differences between the excess brain aging (EBA) as a function of the APOE npscore.

Results

Fig. 2 shows the brain age predictions. Fig. 3 shows that there are significant differences between females and males in the EBA for the APOE npscore <0. Median EBA for both males and females is <0 when APOE npscore <0 suggesting protective effects of ε2 on brain aging. The median EBA >0 for both the sexes when APOE npscore ≥0.

Conclusion

We report sex differences in the influence of APOE genotype on brain aging. There is heterogeneity in the differences within the ε4+ (APOE npscore >0) and ε4‐ (APOE npscore ≤0) groups. These sex differences may not be observed when using just ε4 carrier status instead of the APOE npscore. This provides evidence for a shift in paradigm for the way we analyze APOE genotype because of latent nuances of the ε4‐status influence on AD outcomes.