bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leveraging systems biology approaches and single‐nucleus RNA‐seq to study sex differences in AD
Authors: Brase Logan , Dunn Amy R , Morris John C , Perrin Richard J. , Dumitrescu Logan , Kaczorowski Catherine C. , Hohman Timothy J. , Karch Celeste M. , Harari Oscar , Benitez Bruno A. 
Published: December 2023

AbstractBackgroundThere is increasing evidence indicating sex‐specific patterns in disease manifestation and sex differences in the rates of cognitive decline and brain atrophy. Sex‐related differences in AD‐associated genes are starting to emerge, but these have not been systematically studied at cell‐type‐specific transcriptome‐wide expression levels. We leveraged single‐nucleus RNA‐seq (snRNA‐seq) and systems biology approaches to identify transcriptomic modules in human brains and determine the modules associated with sex‐AD interactions.MethodsWe studied snRNA‐seq data from the parietal cortex of 67 pathologically confirmed controls, sporadic AD (sAD), autosomal dominant AD (ADAD), and other neurodegenerative samples from the Knight ADRC and DIAN cohorts1, and used Celda2 to co‐cluster cells and genes into subpopulations and modules. This approach identified clusters that correspond to previously described cell types1. We used linear mixed models to identify those modules associated with a sex‐AD interaction. For each nominally significant (P<0.05) module, we isolated the top genes that accounted for 80% of the module expression signature and tested each for a sex‐AD interaction.ResultsWhen run on 38,584 astrocytes, Celda split 13,302 genes into 65 gene modules. Module L17 was nominally significant (P = 0.04), with 55 out of 194 genes accounting for ∼80% of the module signature. After multiple testing correction, two genes, ENTREP1/FAM189A2 (Adj.P = 1.57´10−2) and CD38 (Adj.P = 1.80´10−2), showed a significant sex‐sAD interaction in expression (Figure 1, Table 1). ENTREP1 facilitates the removal of the chemokine receptor CXCR4 from the plasma membrane reducing the downstream effects of CXCL12/CXCR4 signaling3 including astrocytic inflammation response4 and release of glutamate as a gliotransmitter5. Studies have linked ENTREP16 and CXCL12/CXCR47 to neurodegeneration. CD38 expression is influenced by cytokine and chemokines released by senescent cells, which increase with age, AD, and other neurodegenerative diseases8. Increased expression of CD38 increases proinflammatory cytokine release and reduces NAD‐dependent enzyme activity, increasing DNA mutations, mitochondrial dysfunction, and oxidative stress. Knockouts of CD38 in mouse showed significant decreases in Aβ plaque load and soluble Aβ levels9.ConclusionThese results suggest that the known neurodegenerative genes ENTREP1 and CD38 are uniquely modulated by biological sex in relation to AD within astrocytes potentially contributing to the clinical differences seen between males and females.
The association of blood‐based biomarkers of neuropathology with cognitive performance and dementia in a diverse, population‐based sample of US adults
Authors: Faul Jessica D , Crimmins Eileen M. , Thyagarajan Bharat , Kim Jung Ki , King Jonathan W , Weir David R , Langa Kenneth M 
Published: December 2023

AbstractBackgroundThe association of blood‐based biomarkers of neuropathology with cognition and dementia, including potential variation by race/ethnicity (whites, blacks and Hispanics), has not been examined in large, diverse, population‐based samples of adults.MethodThe sample included Health and Retirement Study (HRS) respondents over age 50 with blood‐based neuropathology biomarker, demographic, and cognitive data (n = 4,214). A𝛃‐40, A𝛃‐42, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were measured in plasma (Quanterix Neurology 4‐Plex E kit), and phosphorylated tau (pTau‐181) was measured in serum (Quanterix Advantage V2.0 kit). Cognitive tests included immediate and delayed word recall, serial 7s, and backward counting (total score 0‐27). Dementia classification relied on a diagnostic algorithm previously validated in HRS. Linear and unconditional logistic regressions were weighted to account for sample design and used to model associations between the biomarkers and the cognitive score/dementia classification after controlling for age, sex, and batch effects.ResultAbout 80% of the sample was white, 10% black, and 10% Hispanic. Correlations were modest among pTau‐181, NfL, and GFAP (r = 0.29‐0.46).When the biomarkers were analyzed individually, higher A𝛃‐42/A𝛃‐40 ratio was associated with higher cognitive score among whites. Higher NfL was associated with lower cognitive score in the total sample and in each race/ethnic group (whites, blacks and Hispanics). Higher pTau‐181 was associated with lower cognitive score in the total and white sample. Higher GFAP was related to lower cognitive score in the total, white, and Hispanic samples. In a model that included all four biomarkers, GFAP remained significantly related to cognitive performance in the total sample, and NfL remained significantly related to cognitive performance in the total sample and in each race/ethnic group.When the biomarkers were analyzed individually, higher NfL was associated with higher likelihood of dementia in the total sample. Higher pTau‐181 was associated with higher likelihood of dementia among whites. Higher GFAP was associated with dementia in the total and white samples, alone and in the fully adjusted model with all four biomarkers.ConclusionThese results show the importance of examining blood‐based biomarkers of neuropathology as predictors of cognitive performance and dementia in diverse, population‐based samples.
The influence of vascular pathology on the generalizability of machine learning models for cognitive performance estimation
Authors: van Haaften Myrthe F , Yu Jing , Seelaar Harro , Vernooij Meike W , Bron Esther E 
Published: December 2023

AbstractBackgroundImage‐based machine learning models are promising to aid diagnosis in dementia, e.g. by diagnostic classification or estimating cognitive performance. However, the contribution of vascular pathology is often ignored, although many patients have mixed pathologies. This may hamper model generalizability from research setting to clinical practice, as the models are generally developed on populations with lower vascular burden than is encountered clinically. This study aims to evaluate whether model generalizability is influenced by differences in vascular pathology load between training and test groups, represented by white matter hyperintensities (WMHs).MethodWe developed a convolutional neural network to estimate cognitive performance through ADAS13. We included 4791 timepoints from 1632 ADNI subjects. To mimic differences in vascular burden between research and clinical populations, we split the data into a low, middle and high WMH load group using WMH ratio tertiles (WMH volume corrected for intracranial volume). The model was applied to maps derived from T1‐weighted and FLAIR brain MRI using voxel‐based morphometry: model 1 (gray matter density map (GMDM), age, sex), model 2 (GMDM, WMH density map (WMHDM), age, sex) and model 3 (GMDM, log(WMH ratio), age, sex) (Fig. 1). First, we trained all models on the low WMH load group, meaning to test on the high WMH load group to assess generalizability. Second, we trained models 1 and 2 on all data. Mean Absolute Error (MAE) served as the performance metric.ResultThe models trained on the low WMH load group (MAE = 5.08 – 5.41) performed similar to constant value prediction (MAE = 5.63) (Fig. 2, circles). Using all data, models did train successfully (model 1: MAE = 5.64, model 2: MAE = 6.31, constant value: MAE = 7.39) (Fig. 2, crosses). Because of the suboptimal model training in the low WMH load group, especially for individuals with higher ADAS13 scores which were underrepresented in the data (Fig. 3), we could not evaluate generalizability to the high WMH load group.ConclusionThis study was unable to provide new insight into the influence of vascular pathology on the generalizability of machine learning models in dementia. More clinically representative data is needed, covering the full cognitive performance spectrum and higher vascular pathology loads.
Assessment of apathy‐like behaviour in transgenic mouse models of neurodegenerative diseases
Authors: Robinson Lianne , Barraza Maria Cacho , Riedel Gernot 
Published: December 2023

AbstractBackgroundApathy is the most common behavioural and psychological symptom in neurodegenerative diseases like Alzheimer’s disease (AD), frontotemporal dementia (FTD) or Parkinson’s disease (PD). Apathy typically includes a loss of motivation, initiative and interest, listlessness and indifference, flattening of emotions, absence of drive and passion. Scientists have defined this as a reduction/lack in goal direct behaviour. There are currently no specific treatment options for apathy. In experimental models, selective symptoms of apathy‐like behaviour are measured in goal directed or nesting behavioural tasks, which report on their motivation to perform daily activities. A richer understanding of apathy, however, may be achieved through the development of a battery of tests including goal directed, nesting, anhedonia, activity monitoring, and social interaction. These have been applied here to several animal models of neurodegeneration.MethodMale and female transgenic mice (aged 6 – 8 months) including tau over‐expressors L1 for AD and L66 for FTD (Melis et al. 2015); PLB4 BACE1 mouse model for AD (Plucinska et al. 2014); L62 alpha‐synuclein mouse model of PD (Frahm et al. 2018) and relevant wild type (WT) controls were utilised in this study. Animals were tested in a series of behavioural tests including the nest building task, sucrose preference test, buried cookie test, social interaction, and home cage activity. Performance was recorded and analysed by behavioural tracking software as indicators of apathy‐like behaviour.ResultTwo models showed reproducible results compared with previous studies. Intriguingly, L66 FTD mice presented with deficits in sucrose preference and nest‐building, but not a lowering of general activity. Although this was not found for the sister strain, L1 mice which has AD‐like pathology. Very much unexpected is the observation that neither the amyloid nor the synuclein‐based models showed any significant behavioural anomalies. Further detailed investigations are ongoing.ConclusionInitial observations have confirmed that the transgenic models for neurodegenerative diseases show different levels of apathy‐like behaviour. It appears that the phenotype in L66 is a tau‐related anomaly specific to the tau species expressed, i.e. the mutation at P301S. The lack of deficits in all other models warrants in‐depth confirmation and analysis.
Gene‐Based Analysis with Functional Annotation in 2680 South Asians from the LASI‐DAD Study
Authors: Abu‐Amara Hasan , Zhao Wei , Li Zheng , Dey Aparajit Ballav , Zhou Xiang , Lee Jinkook , Kardia Sharon L R , Smith Jennifer A 
Published: December 2023

AbstractBackgroundThe prevalence of dementia among South Asians across India is as high as 10% in those 55 years and older, yet little is known about the risk dementia factors in this population. To date, most known genetic risk loci of Alzheimer’s disease (AD) were identified from studies conducted in European Ancestry (EA) participants. The full mutational spectrum and the functional relevance of those loci in South Asians remains unknown. Analyzing DNA sequence data poses challenges due to the large number of rare variants tested, with most variants likely not associated with dementia. These challenges can be addressed with an annotation‐informed gene‐based analysis.MethodUsing whole‐genome sequence data from 2680 participants from the Diagnostic Assessment of Dementia for the Longitudinal Aging Study of India (LASI‐DAD), we performed a gene‐based analysis of 84 genes known to be associated with AD in EA. We investigated associations with the Hindi Mental State Examination (HMSE) score, general cognitive function, and five cognitive domains. For each gene, we examined missense/loss‐of‐function (LoF) variants and brain‐specific promoter/enhancer variants, separately, both with and without incorporating additional annotation weights (e.g., deleteriousness, conservation scores) using the variant‐Set Test for Association using Annotation infoRmation (STAAR).ResultIn the missense/LoF analysis, when controlling for age, sex, state/territory, and the first 10 principal components, 16 genes were nominally associated with at least one cognitive outcome (p<0.05). Three genes (APOE, PICALM, TSPOAP1) were significant after multiple testing correction (FDR q<0.1). In the brain‐specific promoter/enhancer analysis, 21 genes were nominally significant, but none were significant at FDR q<0.1. Results remained similar after adding annotation weights. The most strongly associated variants in each gene were rs429358 (APOE), rs779406084 (PICALM), and rs9913145 (TSPOAP1). rs779406084 is a missense mutation that is more prevalent in this Indian sample (MAF = 0.075%) compared to EA (MAF = 0.0015%).ConclusionSome genes associated with AD in EA are also associated with cognitive outcomes in South Asians in India. Analyzing sequence data in South Asians provides opportunities to identify potential novel causal variants that are enriched in this population.
Non‐invasive Flicker Neurostimulation Boosts Resilience to Psychological Stress
Authors: Franklin Tina C , Goodson Matthew , Gajelli Tarini , Rutledge Catherine , Tharayil Jacob , Pennebaker Sarah , Naik Arya , Singer Annabelle C , Lab Singer 
Published: December 2023

AbstractBackgroundChronic stress promotes life‐long risk for neuropsychiatric decline by increasing neuroinflammation and disrupting synaptic health and plasticity. Our lab and others have recently demonstrated that non‐invasive gamma sensory flicker stimulation modulates inflammatory signaling, restores microglia function and improves cognitive performance in mice models of Alzheimer’s disease (AD). However, no research to date has studied the effects of flicker in the context of stress. Accordingly, our goal for this study was to determine how sensory flicker stimulation mitigates neuropsychiatric‐like behavioral deficits and rescue glia and synapse pathology following chronic stress.MethodDaily flicker intervention was introduced concomitantly with daily stress exposure (28 days) at multiple frequencies in male and female C57BL6 and Thy1‐GFP mice (n = 6/group per sex). The mice were then tested for anxiety‐like and anhedonia using a range of behavioral tests. Next, we quantified spine density changes in Thy1‐GFP mice and quantified GFAP‐labeled astrocyte morphology change, a reliable proxy for astrocyte reactivity, in the medial PFC using the semi‐automated Imaris imaging software to determine synaptic health and inflammatory profile, respectively.ResultWe show for the first time that stress‐induced morphological changes in the medial PFC are modulated in a sex‐, and frequency‐specific manner that coincides with behavioral resilience in stressed mice. Our findings indicates that audio‐visual flicker protect against stress‐induced behavioral deficits (p<0.0001) and improves neuroinflammation (p<0.01) in a sex‐ and frequency‐specific manner.ConclusionTogether, these findings show frequency tunable flicker intervention improves stress pathology and may prevent neuropsychiatric health decline in conditions with sex dimorphic symptoms and prevalence.
The Emory‐Sage‐SGC TREAT‐AD Center: Tool development for novel targets in Alzheimer’s Disease
Authors: Leal Karina , Axtman Alison D. , Betarbet Ranjita , Brennan Paul E , Carter Gregory W , Fu Haian , Greenwood Anna K , Longo Frank M. , Edwards Aled M , Levey Allan I. , Center The Emory‐Sage‐SGC TREAT‐AD 
Published: December 2023

AbstractBackgroundAlzheimer’s disease (AD) is one of the most prevalent neurodegenerative diseases affecting over 55 million people worldwide. Over the last 20 years, AD research has focused on a limited number of potential drug targets. Given the demonstrated heterogeneity of the disease in biological and genetic components, there is a need to evaluate a broad range of therapeutic hypotheses for target prioritization and development. The Emory‐Sage‐SGC TREAT‐AD Center is generating and openly distributing validated experimental tools necessary to test target predictions generated through sequence‐based characterization of human disease state. We believe that these tools and reagents, including chemical and biological probes that target the multifaceted dysregulation in the brains of AD patients will advance the discovery of potential drug targets for AD.MethodOur Center uses integrated computational approaches to identify target predictions from a set of prioritized therapeutic hypotheses. The current target portfolio was assembled by evaluating prioritized understudied proteins by the Accelerating Medicines Partnership in AD (AMP‐AD) consortium and additional NIA‐supported AD consortia. Nominated targets were evaluated by calculating an unbiased target risk score, literature score, and druggability. Targets are then mapped to 16 biological domains (BDs) that describe and codify the different processes that are dysregulated in AD and prioritized based on multiple lines of evidence for overall AD‐risk. Targets that meet criteria for development are evaluated to identify a set of experimental reagents necessary for hypothesis testing, termed a “target enablement package (TEP).ResultWe have prioritized more than 30 understudied targets for TEP development. For each understudied target, a TEP includes expression constructs, purified protein and methods, validated knockout cell lines, and antibody validation. All reagents are developed to meet established quality criteria. For a subset of tractable targets additional TEP components include assay development, crystal structures, screening, and probe development. Advanced targets include SYK, DDX1, SFRP1, SDC4, ARHGEF2, and CAPN2. TREAT‐AD investigators place all data, knowledge, reagents, and tools into the open domain with no intellectual property claims.ConclusionAll data, protocols, reagent sets, and chemical tools will be made widely available on the AD Knowledge Portal. For more information see www.treatad.org.
Microglial phenotype and proinflammatory gene induction in human prefrontal cortex in Alcohol Use Disorder overlap with Alzheimer’s Disease
Authors: Crews Fulton Timm 
Published: December 2023

AbstractBackgroundAlcohol Use Disorder (AUD) and heavy alcohol abuse are associated with dementia. However, studies focused on Alzheimer’s disease (AD) tend to exclude heavy alcohol drinking patients. We hypothesize microglial phenotype changes in AUD contribute to degeneration that parallels AD.MethodOrbital frontal cortex (OFC) from moderate drinking controls and heavy drinking AUD individuals paired by age were obtained from the New South Wales Tissue Resource Center in Sydney Australia. Tissue blocks were used for RTPCR gene mRNA and paraffin sections for immunohistochemistry assessment of microglial and proinflammatory genes and proteins, respectively. Fluoro‐Jade B, TUNEL stain and neuron marker NeuN were used to assess degeneration.ResultAUD OFC expressed increased levels of proinflammatory HMGB1, RAGE, and multiple Toll‐like receptors (TLR). In addition, AUD OFC increased expression of the TLR adaptor protein myeloid differentiation primary response 88 (MyD88), NFκB, and proinflammatory cytokines, chemokines, and their corresponding receptors. Iba1, a marker of monocytes and microglia, is increased in AUD, but not mRNA levels. Macrophage‐1 antigen, a complement receptor, is increased in AUD cortex as is CX3C chemokine receptor 1 (CX3CR1), the fractalkine receptor. OX42 staining (CD11b) in also increased. Microglial markers P2ry12, and CSF1R also show greater cellular staining in human AUD. The lysosomal scavenger receptor marker CD68 is also increased in AUD cortex. CX3CR1 and CD11b mRNA are increased in AUD cortex, but not CD68. Interestingly, TMEM119, a specific microglial marker, is decreased in AUD, both mRNA and protein staining in contrast to other markers increasing. Assessment of DNA oxidation using 8‐hydroxy‐2'‐deoxyguanosine (8‐OHdG) a biomarker of oxidative DNA/RNA damage 8‐OHdG+IR indicated AUD more than doubled cortical cells with this marker. Induction of HMGB1‐TLR‐MyD88‐NFκB proinflammatory signaling pathways, oxidative stress and microglial activation correlate with markers of neurodegeneration.ConclusionThe increased expression of TLR receptors, MyD88 and NFkB and increased proinflammatory cytokines are consistent with increased microglial activation and oxidative stress induced degeneration. Studies support alcohol activated microglia‐monocytes as driving loss of NeuN and other neurodegeneration markers. The reduced TMEM119 level with other markers increasing may indicate monocytes are replacing microglia in AUD cortex.
Exploring Predictable CSF derived biomarkers between mutation carriers and noncarriers in autosomal dominant Alzheimer’s disease
Authors: Shen Yuanyuan , Morris John C , Llibre‐Guerra Jorge J , Karch Celeste M. , Xiong Chengjie , Perrin Richard J. , Renton Alan E. , McDade Eric , Bateman Randall J. ,   Dominantly Inherited Alzheimer Network (DIAN), Cruchaga Carlos 
Published: December 2023

AbstractBackgroundAutosomal dominant Alzheimer’s disease (ADAD) is caused by known genetic mutations that start a cascade of events leading to Aβ deposition, tau pathology and neurodegeneration. Mutation carriers (MCs) are characterized by substantial amyloid accumulation, and dementia onset at or around the age of parental dementia onset. CSF, plasma Aβ, tau and ptau are well known biochemical biomarkers for AD. However, other proteomic changes associated with ADAD have not been explored in a systematic manner. Here, we generated high‐throughput CSF proteomic data from MCs and noncarriers (NCs), and identified proteins associated with mutation status and estimated years to symptom onset (EYO), in Dominantly Inherited Alzheimer Network (DIAN).MethodA total of 7,011 CSF proteins measured with the SomaScan 7k platform passed QC and Lumipulse assays from in 476 DIAN participants: 281 MCs, 185 NCs. We utilized linear models with participants’ status, age, gender and surrogate variables to identify proteins associated with mutation status. Then, predictable trajectory intersection of EYO between MCs and NCs were identified. We applied enrichment analysis to evaluate biological functions of significant proteins.ResultWe identified 243 significant proteins (FDR < 0.05) associated with status. The ‘Established’ AD biomarkers, phospho‐Tau181, Tau, neurofilament light polypeptide, Aβ42 were our top 5, 19, 25and 33 hits. The top 10 proteins included SMOC1, 14‐3‐3 proteins, SLIT2 or DNAJB9. Through the EYO trajectory intersection, we found several proteins with trajectory changes earlier than Aβ (‐11.0 years) or NEFL (‐11.6 years); these include SMOC1 and 14‐3‐3 proteins, with changes ‐30.7 and ‐13.5 years before the estimated symptomatic onset. Gene ontology analysis suggested that the identified proteins were enriched in axon development, axonogenesis and neuron projection morphogenesis. Alzheimer disease and pathways of neurodegeneration were identified by KEGG pathway gene set enrichment. The identified proteins were enriched in astrocytes, macrophages and neurons by cell marker analysis.ConclusionOur analyses identified 243 proteins associated with ADAD mutation status. Of these 93% of them change before the estimated symptomatic onset and could be leveraged to better predict the year of symptom onset. The enrichment analysis revealed the identified proteins may closely associated with the development of Alzheimer disease.