bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved SUVR calculation for [18F]‐AV45 amyloid pet imaging using a novel reference region approach
Authors: Pfeil Julia , Drzezga Alexander , van Eimeren Thilo , Bischof Gerard N 
Published: June 2023

AbstractBackgroundUtilization of a data‐driven approach to find a more sensitive reference region (RR) for [18F]‐AV45 PET imaging that differentiates the spectrum of Alzheimer’s disease (AD) and improves especially longitudinal study designs.MethodData of 283 participants (135 amyloid‐negative cognitively normal (CN), and 148 amyloid‐positive AD) from the ADNI database (http://adni.loni.usc.edu/) was used. All [18F]‐AV45 scans were co‐registered, normalized, and skull‐stripped. The dataset was split into a training‐and test‐dataset. Voxel‐wise group comparisons were performed in the training‐set (75 CNs, 77 ADs) to identify a RR that is void off on‐target tracer uptake. Potential clusters were used to extract mean global SUVRs in the test‐dataset (60 CNs, 70 ADs). Effect sizes between novel and commonly used RRs were compared. Baseline and follow‐up data of 19 CNs, 36 participants with mild cognitive impairment, and 26 ADs was used to test whether the newly identified RR is more sensitive to assess longitudinal change than common RRs. Effect sizes of change in SUVR between baseline and follow‐up were used as metric of sensitivity.ResultThe training dataset yielded two novel RRs in the brainstem and the cerebellar white matter. These new RRs showed higher effect sizes compared with commonly used RRs. However, no significant differences in the effect sizes were observed when examining longitudinal change in SUVR compared with commonly used RRs.ConclusionThe data‐driven approach did not improve SUVR measurements for [18]‐AV45 imaging. However, our analyses proved that the commonly used RRs are also longitudinally stable and sensitive to differentiate clinical from non‐clinical groups.
Role of Amyloid Precursor Protein in Astrocytes in Alzheimer´s Disease.
Authors: Jauregui Gretsen Velezmoro ,   Translational Neuroscience and Aging Program (TAP)
Published: June 2023

AbstractBackgroundAstrocytes are specialized glial cells that when exposed to inflammatory factors go through a process known as reactive astrogliosis. Reactive astrocytes are a neuropathological feature of Alzheimer’s disease (AD). The etiology of AD is often explained by the accumulation of β‐amyloid peptides, a proteolytic product of the amyloid precursor protein (APP). However, inflammation also plays a prominent role in the development of AD. How reactive astrocytesparticipate in the pathogenesis of AD remains poorly understoodMethodTo elucidate the role of astrocytes in the pathogenesis of AD we exploited different in vitro and in vivo models to investigate the role of Amyloid Precursor protein in setting the immune response of astrocytes.ResultOur results show that overexpression of APP in human cortical astrocytes induces reactive phenotype, similar to astrocytes found in brains of AD patients. These reactive astrocytes produce significantly increased levels of INF‐g in comparison with control astrocytes. Similar positive correlation between APP levels and INF‐g is found also in astrocytes from AD transgenic and traumatic brain injury mice models.ConclusionOur data indicate that astrocytes are activated by high levels of APP, which promotes production and secretion of interferons and recapitulates salient features of astrocytes in AD.
Brain‐derived neurotrophic factor genes are associated with neuropsychiatric symptom progression in dementia. The Cache county dementia progression study
Authors: Matyi Joshua , Drewel Mikaela , Schwartz Sarah , Rattinger Gail B. , Gonzalez Hector Leonardo , DeBerard Scott , Buhusi Mona , Lyketsos Constantine G. , Tschanz JoAnn T 
Published: June 2023

AbstractBackgroundPolymorphisms in genes coding for the neurotrophin, brain‐derived neurotrophic factor (BDNF) or its receptors, have been associated with Alzheimer’s disease and related disorders (ADRD), with sex‐dependent effects. Associations with neuropsychiatric symptom (NPS) progression after dementia onset has been largely unexplored. In a population‐based cohort, we examined the relationships between BDNF gene single‐nucleotide polymorphisms (SNPs) and NPS progression after dementia onset.Method880 participants [61.3% female; mean (SD) age = 82.0 (71) years] with dementia [68.2% AD; 13.5% Vascular Dementia (VaD); 18.3% other dementia (OD)] were assessed on the Neuropsychiatric Inventory (NPI) every six‐to‐18 months. Mean(SD) baseline dementia duration was 2.9(2.7) years. The following SNPs were examined as predictors of NPI scores over time in linear mixed‐effects models: rs6265 (BDNF G196A/Val66Met), rs56164415 (BDNF C270T), rs2289656 (NTRK2 receptor TrkB), and rs2072446 (NGFR p75NTR). Covariates included age of dementia onset, education, apolipoprotein E genotype, and dementia type and duration at baseline.ResultSex‐dependent effects were found for two SNPs. Compared to those with major alleles, males with the rs56164415 minor allele exhibited a lower initial Apathy score, that increased over time (C/t*sex*time2:b = ‐0.063, SE = 0.029, p = .033); by contrast, females showed no differences by SNP alleles. Females homozygous for the rs2289656 minor allele exhibited a rapid increase in Anxiety that decreased over time (t/t*sex*time2: b = ‐0.145, SE = 0.054, p = .0073). For both sexes, presence of minor alleles for BDNF polymorphisms rs6265 (G/a*time2: b = ‐0.017, SE = 0.004, p < .001; a/a*time2: b = ‐0.035, SE = 0.013, p = .006) and rs56164415 (C/t*time2: b = 0.019, SE = 0.005, p < .001) was associated with increased NPI Agitation/Aggression well after baseline. Rs6265 minor allele homozygotes (a/a*time2: b = ‐0.049, SE = 0.013, p < .001) and rs2072446 minor allele carriers (Ct/tt*time2: b = ‐0.012, SE = 0.005, p = .025) exhibited initial increases in Delusions, which diminished approximately 5 years thereafter.ConclusionSpecific BDNF genotypes were associated with NPS presentation after dementia onset, with some sex‐dependent effects. Future research on enhancing BDNF signaling may present possible targets for intervention.
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

AbstractBackgroundHypertension 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.MethodsA 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.ResultsCompared 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.ConclusionOur 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

AbstractBackgroundThe 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.MethodParticipants 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.ResultThe 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).ConclusionThere 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

AbstractBackgroundAge 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.MethodA 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.ResultThe 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.ConclusionA 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

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

AbstractBackgroundIrisin 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.MethodPrimary 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.ResultWe 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.ConclusionThese 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

AbstractBackgroundThe 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.MethodWe 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.ResultThe 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).ConclusionMRI 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.