bluuebunny/crossref_metadata_2025_split huggingface dataset:
Elevated levels of CSF p‐tau212 in FTLD‐Tau
Authors: Kac Przemyslaw Radoslaw , Cousins Katheryn A Q , Shaw Leslie M. , Irwin David J , Karikari Thomas K , Turton Michael , Deerlin Vivianna M Van , Harrison Peter , McMillan Corey T , Wolk David A , Lee Eddie B , Blennow Kaj , Zetterberg Henrik 
Published: January 2025

AbstractBackgroundPhosphorylated‐tau (p‐tau) biomarkers are typically specific for Alzheimer’s disease (AD) and are less elevated in the cerebrospinal fluid (CSF) of frontotemporal lobar degeneration (FTLD) type tau (FTLD‐tau). FTLD is a pathologically and clinically heterogenous neurodegenerative disorder, and we currently lack biomarkers to differentiate the two major pathological subtypes 1) FTLD‐tau, where pathological tau aggregation is observed or 2) FTLD‐TDP, where TAR‐DNA binding protein 43 (TDP‐43) is linked with the disease development and progression. Because FTD clinical phenotype does not predict pathology, biomarkers sensitive to FTLD‐tau are needed to provide a biological diagnosis in life. In this study, we test CSF p‐tau212 in patients with autopsy‐ or mutation‐confirmed FTLD‐tau and FTLD‐TDP without AD pathology; clinically healthy individuals without cognitive impairment and autopsy‐confirmed Lewy body disease with alpha‐synuclein (αSyn) were included as reference groups.MethodAutopsies were performed at the University of Pennsylvania in the Center for Neurodegenerative Disease Research. Definite diagnosis was based on autopsy results or determined genetically. Using SIMOA technology, we tested p‐tau212 in 51 healthy controls, 33 FTLD‐Tau, 36 FTLD‐TDP and 13 αSyn (Figure 1). For further analysis we excluded individuals with evidence of AD pathology: intermediate/high AD neuropathologic change (ADNC), Thal phase ≥2, or CSF β‐amyloid 1‐42 ≤192. Wilcoxon test was used to compare groups. In brain regions sampled at autopsy, pathological tau burden was rated using a semi‐quantitative 5‐point scale; Spearman correlations tested associations between p‐tau212 and tau burden by region.ResultCSF p‐tau212 was significantly increased in FTLD‐Tau when compared to healthy controls, people with FTLD‐TDP and people with αSyn pathology (Figure 2). Results remained significant when people with evidence of AD pathology were excluded. P‐tau212 measurements strongly correlated with tau burden across multiple brain regions (Figure 3). Average correlation was r=0.57, p<0.0001.ConclusionCSF p‐tau212 is strong candidate biomarker to differentiate FTLD‐tau from FTLD‐TDP and αSyn.
Inflammation and cytoskeleton pathway gene expression relates to rate of clinical progression in individuals with Alzheimers disease
Authors: Bebek Gurkan , Kim Hyun Jo , Benchek Penelope , Bekris Lynn M. , Leverenz James B , Bush William S. , Pillai Jagan A. 
Published: January 2025

AbstractBackgroundInflammatory changes are a key element of Alzheimer’s disease (AD)pathophysiology. However, there is lack of clarity regarding key gene drivers of the cytokines identified as playing a role in clinical AD progression and their relationship to AD biomarkers to understand their clinical role.MethodWe investigated transcriptomic datasets from Alzheimer’s Disease Neuroimaging Initiative (ADNI) and Harvard Brain Tissue Resource Center (HBTRC) to evaluate regulatory gene networks in human AD. We hypothesized that key inflammatory genes are differentially upregulated in AD, predicting clinical progression. ADNI peripheral blood transcriptomic data with cerebrospinal fluid (CSF) AD biomarker confirmed diagnosis was available for 30 AD dementia, 95 MCI, and 41 controls. This was next compared against HBTRC dorsolateral pre‐frontal cortex tissue gene expression data from 376 AD dementia and 173 controls with neuropathology confirmed diagnosis. The association between differentially expressed genes (DEGs) and change in cognition from baseline in ADNI, measured by clinical dementia rating scale ‐sum of boxes (CDR‐SB) at baseline 6, 12, 24 and 36 months using a linear mixed model (LMM) with random intercepts.ResultWe identified 170 DEGs between AD and controls common to ADNI and HBTRC. Among the DEGs, canonical inflammation signaling pathway genes were enriched. Using an FDR cutoff of 0.15, five genes (DUSP13, ANK1, SPTB, SLC6A and DMTN) were associated with significant CDR‐SB change from baseline in MCI and AD. Four of these genes were highly correlated (r2 > 0.8) and were involved in the Spectrin‐associated cytoskeleton pathway (GO:0014731). Among them, increased expression of DUSP13 in AD compared to controls (log2FC = 0.17) was associated with an increased decline in cognition (P = 0.001). An increased expression of ANK1 was related to reduced decline in cognition (P = 0.002) and ANK1 expression was lower in AD compared to MCI (log2FC = ‐0.16). CDR‐SB models incorporating gene expression for these significant genes were equivalent to or better than models incorporating CSF pTau, Aβ42, or MRI hippocampal volume when evaluated by Akaike information criterion.ConclusionKey peripheral inflammation and cytoskeletal gene expression relates to clinical progression in human AD. Validation of these results is an important future direction.
Association of synaptic density and neurofibrillary tau in preclinical and clinical Alzheimer’s disease
Authors: DiFilippo Alexandra H , Christian Bradley T. , Jonaitis Erin M. , McLachlan Max , McVea Andrew K , Bettcher Brecca , Schulz Nicholas R , Pasquesi Mary‐Elizabeth , Davenport‐Sis Nancy J , Thor Yer , Grover Ethan , Barnhart Todd E , Engle Jonathan W , Betthauser Tobey J. , Johnson Sterling C. , Bendlin Barbara B. 
Published: January 2025

AbstractBackgroundSynaptic density loss is a major correlate of cognitive functioning in adults with and without significant impairment. It is also a feature of clinical Alzheimer’s disease (AD) and suspected to co‐occur with neurofibrillary tau (NFT) accumulation. Previous studies using [11C]UCB‐J for in‐vivo analysis of synaptic density have been restricted to unimpaired (CU) A‐ and impaired (CI) AD (A+) participants where within group analyses have shown no association between synaptic density and NFT. There is also little known about the relationship between synaptic density and NFT in AD without cognitive impairment. Here we evaluated the association between synaptic density and NFT in CU and CI AD.MethodParticipants were recruited from ongoing AD‐related studies (Wisconsin Registry for Alzheimer’s Prevention, ADRC) at UW and from the community and underwent comprehensive clinical and cognitive evaluation to determine cognitive status. Pearson’s r was used to determine associations between synaptic density ([11C]UCB‐J DVR) and neurofibrillary tau ([18F]MK‐6240 SUVR) across all participants and within amyloid and cognitive groups.ResultParticipant demographics are reported in Table 1. Across all participants, synaptic density and ERC, Hp NFT were well correlated (ERC NFT: r = ‐.46, p < .001; Hp NFT: r = ‐.49, p < .001). Within groups, only the CU A+ correlation between synaptic density and NFT remained significant (ERC NFT: r = ‐.49, p = .02; Hp NFT: r = ‐.59, p = .003) with CI A+ showing only a moderate (insignificant) relationship with Hp NFT (ERC NFT: r = ‐.16, p = .44; Hp NFT: r = ‐.31, p = .14) (Figure 1).ConclusionIn agreement with previous work, CI AD has lower Hp synaptic density than CU A‐, and no significant relationship between Hp synaptic density and NFT. However, CU AD participants showed a significant relationship between NFT and synaptic density. This may be explained by a floor effect of Hp synaptic density that is reached by participants with clinical AD, but not yet in preclinical AD, or the existence of non‐AD pathologies contributing to synapse loss. These results can help better understand the process of neurodegeneration in AD as participants progress from preclinical to clinical AD.
Sex‐specific topological structure associated with dementia identified via latent space network analysis
Authors: Wang Selena , Wang Yiting , Xu Fredericks , Shen Li , Zhao Yize 
Published: January 2025

AbstractBackgroundStatistical network analysis has transformed neuroimaging research in recent years by enabling flexible and intuitive integration of multiple data types and preserving the topological brain connectivity structure while uncovering mechanism of degenerative aging. In this study, we apply a novel latent space joint network model to perform a case‐control comparison using the functional connectivity data together with region‐specific cortical volume, cortical thickness, surface area and PET information. By preserving complex network structures during imaging biomarker detection, we find sex‐specific topological structures associated with dementia.MethodWe used resting state functional neuroimaging data from the ADNI study collected from 406 subjects, 208 males and 198 females. Of these, 198 subjects are healthy; 158 subjects show mild cognitive impairment; and 55 subjects show symptoms of dementia. To capture the group‐level functional connectivity information, the proposed method extends the latent space model to accommodate multiplex brain network structure and identify significant imaging biomarkers by comparing group‐level connectivity between healthy, MCI and dementia patients.ResultFor female subjects, areas of connectivity edges that are impacted by dementia and MCI tend to following the organizational topological structure of the brain (Figure 1). In contrast, areas of connectivity edges that are impacted by dementia and MCI for the male subjects do not follow such structures (Figure 2). Furthermore, we found that, among the female subjects, the difference between healthy and patient population tends to be larger for central actors of the network, brain regions of high node strength (Figure 3A and B). In Figure 3C, we see that, for females, there seem to be differences in brain connectivity among different types of imaging biomarkers, but not for males. For females, strong connectivity edges tend to indicate the development of dementia; whereas, for males, there is no such trend.ConclusionThe proposed latent space joint network model is designed to capture brain topological structure while performing statistical inference. This initial AD functional connectivity study demonstrates the promise of uncovering the topological structure associated with degenerative aging and foster future investigations of the underlying mechanisms between network structures and data modalities and provide a new lens to disease pathology.
Sex, racial/ethnic, and APOE‐ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging
Authors: Peterson Amalia Jo , Sathe Aditi , Yang Yisu , Durant Alaina , Shashikumar Niranjana , Pechman Kimberly R. , Dumitrescu Logan C. , Gifford Katherine A. , Risacher Shannon L. , Beason‐Held Lori L , An Yang , Schilling Kurt , Landman Bennett A. , Schneider Julie A. , Barnes Lisa L. , Bennett David A. , Jefferson Angela L. , Resnick Susan M , Saykin Andrew J. , Hohman Timothy J. , Archer Derek B. ,   the Alzheimer's Disease Neuroimaging Initiative (ADNI)
Published: January 2025

AbstractBackgroundThere is growing recognition that white matter microstructural integrity is affected in Alzheimer’s disease. The goal of this study was to characterize sex, racial/ethnic, and apolipoprotein (APOE)‐ε4 allele differences in white matter integrity.MethodsThis study included participants from ADNI, BLSA, ROS/MAP/MARS, and VMAP, all longitudinal cohorts of aging. This combined dataset included 6,837 imaging sessions from 2,619 participants age 50+ with diffusion MRI (dMRI) and demographic and clinical data (60% female, 31.4% APOE‐ε4 carriers, 78.9% White). dMRI was preprocessed using the PreQual pipeline. Free‐water (FW) correction was used to generate FW and FW‐corrected intracellular metrics including fractional anisotropy (FAFWcorr), mean diffusivity (MDFWcorr), axial diffusivity (AxDFWcorr), and radial diffusivity (RDFWcorr). Conventional and FW‐corrected metrics were harmonized using the Longitudinal ComBat package. Linear mixed‐effects models related sex, race/ethnicity, and APOE‐ε4 allele status to longitudinal diffusion metrics in 48 white matter tracts, adjusting for age at baseline, sex, education, race/ethnicity, APOE‐ε4 carrier status, cognitive status at baseline, and converter status. All models were corrected for multiple comparisons using the FDR approach.ResultSex differences in white matter were most notable in projection tracts (Figure 1A) and were primarily in FW‐corrected metrics. Females had lower FAFWcorr and higher RDFWcorr, indicative of worse microstructure, but lower AxDFWcorr. This sex difference was most pronounced for FAFWcorr in the ventral premotor projection tract (p=1.53x10‐62). There were global differences in white matter integrity by race/ethnicity (Figure 1B). Non‐Hispanic White participants tended to have higher conventional FA, FAFWcorr and AxDFWcorr and lower RDFWcorr. There was no association between APOE‐ε4 status and white matter integrity and no significant sex x race/ethnicity, sex x APOE‐ε4, or race/ethnicity x APOE‐ε4 interactions for conventional or FW‐corrected metrics when corrected for multiple comparisons.ConclusionThere were striking sex and racial/ethnic (but not APOE‐ε4) differences in white matter tract integrity in a large cohort of aging adults. Female participants tended to have measures reflective of worse white matter integrity, and non‐Hispanic White participants tended to have measures reflective of greater integrity. Additional research exploring the etiology of these differences will be important to better understand disparities in Alzheimer’s disease.
Modulating γ‐secretase activity to make precision medicine for AD
Authors: Chávez‐Gutiérrez Lucia 
Published: January 2025

AbstractGamma‐secretases play a pivotal role in the generation of Aβ peptides. Mutations in these enzymes that cause early‐onset, autosomal dominant AD shift Aβ production towards generation of longer peptides. We have recently shown that the mutation‐induced shifts in the ratio of short‐to‐long Aβ peptides not only inform about mutation pathogenicity but also allow experimental prediction of the age at dementia onset. This observation argues in favor of therapeutic strategies that shift Aβ production towards the generation of shorter and non‐toxic Aβ peptides.By stabilizing GSEC‐APP interactions and activating the GSEC processive cleavage of APP, GSEC modulators (GSMs) have the potential to selectively reduce the levels of longer and toxic Aβ peptides, without hindering essential cellular processes that depend on the overall GSEC proteolytic activity. GSMs thus offer a nuanced approach to prevent, and potentially slow down, amyloid‐driven neurodegenerative cascades in AD therapy. However, thorough mechanistic investigation of the modulatory actions of GSMs on GSEC activities and biology is paramount to unlock the full therapeutic potential of GSMs in the clinic.I will present and discuss our latest mechanistic studies of GSEC (dys)function and its modulation by GSMs acting as GSEC‐APP stabilizers.
targeting gamma‐secretase in the Dominantly Inherited AD patients
Authors: McDade Eric 
Published: January 2025

AbstractAlthough amyloid b immunotherapies offer great potential for prevention or delay of symptoms in dominantly inherited AD (DIAD), the mechanism of action of this class of medications does not address the underlying mechanism of most DIAD mutations. Moreover, the need for repeated IV infusions or sub‐cutaneous injections with Ab immunotherapies may prove challenging for long‐term prevention approaches. The majority of DIAD mutations appear to affect the interaction of the gamma‐secretase enzyme with the Amyloid Precursor Protein (APP) making this enzyme an attractive target for disease modification. However, emerging evidence also suggests that different DIAD mutations can have significantly different effects on the processing of APP, which suggests that targeting this enzyme may have mutation dependent effects as well.Developments in the understanding of the timing of amyloid b‐dependent changes in DIAD and the development of accurate measurements of Ab now enable precision‐based approaches necessary for targeting gamma‐secretase. Moreover, the presence of clinical trial platforms for DIAD facilitate the implementation of trials for targeting gamma‐secretase.In this session, we will review approaches to testing next generation gamma‐secretase therapies in DIAD. Specifically, we will outline prevention approaches in DIAD that leverage fluid‐based biomarker measurements of Ab ‐peptides and sensitive, brief cognitive assessments to determine optimal mutation specific dosing approaches‐ i.e. precision medicine approach. Combining plasma, CSF and molecular PET imaging, we will outline how to assess gamma‐secretase targeting therapies for different mutations in DIAD along a timescale that utilizes early pharmacodynamic effects on Ab ‐peptides to predict long‐term effects on Ab ‐and downstream biomarkers of AD.
what would be needed to start a real primary prevention trial in Alzheimer’s Disease
Authors: Mummery Catherine J. 
Published: January 2025

AbstractAnti‐amyloid therapies are ideal candidates for prevention trials. Secondary prevention in those at risk of ADAD (DIAN‐TU) has shown reduction of brain amyloid deposition leads to significant downstream biological change; early secondary prevention using a monoclonal antibody in sporadic AD (AHEAD 3‐45) is ongoing and will provide critical information on whether treating earlier leads to greater clinical benefit. However, this is not preventing disease but delaying onset in those with presymptomatic disease.True primary prevention can be defined as treating before any evidence of disease, i.e. amyloid or tau pathology. So how do we identify that stage in sporadic AD? In addition, what is the best mechanism to target for primary prevention? Decreasing production of abeta is a prime candidate.While there is sound logic in treating prior to disease onset to prevent the disease cascade commencing, there are significant ethical and practical challenges in optimising a prevention trial design. To design a true primary prevention trial in AD, one needs to identify reliably individuals at high risk of developing AD prior to pathology developing. A clear risk triage strategy would be required, alongside development of predictive biomarkers for disease. We need to understand early biological triggers/progression better to be able to define an at risk population and likely timescale to onset of disease. We will need to consider how long to treat for – if not a one‐off treatment, does this potentially commit someone to lifelong treatment? Outcome measures need to be designed to determine the success of a preventative rather than treatment strategy. There have been significant advances in blood biomarkers, but more sensitive clinical and biological markers of early disease onset are required. These trials will be long in duration and require large numbers of participants to commit years to show a treatment effect.We are at the beginning of prevention trials in AD. In order to succeed, there must be close collaboration between discovery science, industry, the trials community and regulatory bodies to agree a framework that provides the best chance of optimising trial design and maximizing chances of success.
A Novel Blood Based Mitochondrial Biomarker for Alzheimer’s Disease
Authors: Hauger Brittany M , Smith Keith P , Strope Taylor A. , Oehmke Ellen , Kueck Paul J , Kemna Riley E , John Casey S. , Bantis Leonidas , Morris Jill K , Swerdlow Russell H , Wilkins Heather M 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) pathology begins decades before clinical onset of dementia. Amyloid beta (Aβ) generally accumulates first in cognitively normal (ND) individuals, with tau and cognitive abnormalities following. AD pathologies have been found to correlate and interact with metabolic and mitochondrial outcomes in studies spanning numerous experimental paradigms. Targeting metabolic and mitochondrial function in clinical trials is an emerging theme for AD and highlights the importance and need for biomarkers which measure mitochondrial function.Method20 ND, 20 mild‐cognitive impairment, and 19 Alzheimer’s Disease (AD) subjects were recruited from the KU Alzheimer’s Disease Research Center Clinical Cohort. Blood was collected in ACD tubes. Lymphocytes were isolated using Accuspin tubes, histopaque 1077, and centrifugation. Lymphocytes were stained with MitoTracker/Annexin V, MitoSox/Hoechst, and TMRE/Hoechst. Fluorescent cells were quantified using flow cytometry and values normalized to Hoechst. Fluorescent measures were completed within 30 hours of blood draw. The mitochondrial health index (MHI) algorithm was calculated. Plasma NfL, pTau181, Aβ, and GFAP were determined using SIMOA. APOE genotypes were determined using a Taqman allelic discrimination assay.ResultThe MHI biomarker was significantly reduced in AD subjects and tracked with mini mental state exam (MMSE) scores. APOE ε4 carriers had reduced MHI regardless of diagnosis. Plasma GFAP, NfL, and pTau181 were increased in AD subjects. ROC analysis for individual biomarkers for ND/AD: Aβ 0.6658, GFAP 0.7194, NfL 0.7194, pTau181 0.7796, MHI 0.8028. ROC analysis for individual biomarkers for ND/MCI: Aβ 0.6700, GFAP 0.5737, NfL 0.5368, pTau181 0.7105, MHI 0.6025. ROC analysis for individual biomarkers for MCI/AD: Aβ 0.5632, GFAP 0.5965, NfL 0.6462, pTau181 0.5078, MHI 0.8139.ConclusionThe MHI biomarker is a blood‐based biomarker with reasonable discrimination for AD diagnosis. Further studies are needed to fully understand how these potential biomarkers associate with disease progression and vary over time. However, mitochondrial biomarkers are urgently needed to assess therapeutic validity in upcoming clinical trials.