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Background Alzheimer’s Disease (AD) is a complex disease with varying etiology based on genetic, environmental, and social factors. Most of the literature in the field has focused on studying AD in individuals with European ancestry. Recent efforts have shown that AD and related diseases show differences based on ethnicity. Our previous work has demonstrated variable allele frequency in the top ten risk alleles between Mexican American and Non‐Hispanic White Americans in the Health and Aging Brain Study‐ Health Disparities (HABS‐HD). It is essential to study AD in minorities, who are estimated to experience significantly increased disease burden in the next few decades. Method To expand our previous work, we conducted a pilot Polygenic Risk Score (PRS) study on N = 665 Mexican Americans from the HABS‐HD Study with complete phenotype data. Using quality controlled and cleaned genotype data from these individuals, PRSice was used to construct a PRS model using age, gender, APOE E4 status, and the first 5 Principal Components as covariates. Generalized Linear Regression was used to predict association between the PRS results and the predicted phenotype (AD). AUC was calculated for both the APOE E4‐only model and the full model. Result The pilot PRS model performed well on N = 665 Mexican Americans from HABS‐HD, with a R^2 best fit at P – value threshold = 0.01555. The ROC graph shows AUC of 0.605 for PRS with covariates and 0.54 without covariates. Conclusion Our pilot study shows that a PRS produced for this population can accurately predict disease phenotype. We plan to conduct larger examinations of this nature and further elaborate on minority health disparities in order to fill the gaps in the literature and expand our understanding of genetic risk in various ethnic groups.

Background White matter hyperintensity (WMH), which is considered a sign of vascular lesions, is often found in patients with DLB, but its association with vascular lesions has not been proven. We assessed WMH in patients with DLB and markers of vascular damage and vascular risk factors. Method We examined 78 patients that fulfilled clinical criteria of DLB. The clinical assessment included MoCA, MMSE, ACE‐R, IQCODE, NPI‐4, UM‐PDHQ, UPDRS‐III, RBD1Q, orthostatic hypotension test. All patients underwent 1,5 T brain MRI. WMH was evaluated with Fazekas score and ARWMC. Patients were performed ultrasound assessment of flow‐mediated vasodilation. Laboratory investigation included Willebrand factor, lipid profile, microalbumin/creatinine ratio. Result MRI revealed with moderate to severe WMH in 43 participants. There were no significant differences in vascular risk factors, vessel reactivity, laboratory results between patients with or without WMH. These findings were associated more likely with hyppocampal atrophy and disease duration than vascular risk factors. Conclusion WMH in DLB may be associated with neurodegenerative pathology. Further investigations with diffusion MRI techniques and prospective studies can be helpful in interpretation of neuroimaging findings and understanding of its contribution to the course of the disease.

Background To guide blood biomarker implementation to detect Alzheimer’s disease (AD), evaluations in clinically and racially diverse samples are needed. Here, we compare plasma biomarkers phosphorylated tau 217 (p‐tau217), β‐amyloid (Aβ) 1‐42/1‐40 (Aβ42/Aβ40) ratio, and p‐tau217/Aβ42 ratio in a University of Pennsylvania (UPenn) sample that includes self‐identified White and Black/African American individuals with and without cognitive impairment, and independently validate findings in the first 100 AD Neuroimaging Initiative (ADNI) autopsy participants. Methods UPenn inclusion criteria were plasma p‐tau217, Aβ42, and Aβ40 (n = 213) assayed using the automated Fujirebio platform, self‐reported race (156 White [including 1 Hispanic White, 2 multiracial] and 57 Black), and 18F‐florbetaben PET scan to determine Aβ positivity by visual read (87 Aβ+, 126 Aβ‐). Participants were cognitively Normal (n = 128) or Impaired (n = 85) according to National Alzheimer’s Coordinating Center (NACC) Uniform Dataset 3.0 criteria. Linear models tested if plasma biomarkers (dependent variable, log‐transformed) differed by race and/or Aβ PET status (±). To confirm observed racial differences, linear models tested the interaction of race by global Aβ PET standardized uptake value ratio (SUVR). Models covaried for age at plasma, sex, 2021 national area deprivation index (ADI), and APOE ε4. Receiver operating characteristic (ROC) with bootstrapping (2000 iterations) compared biomarker performance (area under the curve [AUC]) and calculated 2 thresholds at 0.95 sensitivity and 0.95 specificity. Plasma p‐tau217 cutpoints were validated in ADNI autopsy sample (n = 100); high/intermediate AD neuropathologic change considered AD+. Results P‐tau217/Aβ42 had the highest performance to discriminate Aβ+ from Aβ‐ (Table 1A,1B; all AUC≥0.90), and p‐tau217 showed excellent accuracy in ADNI sample (0.96; Table 1B). Linear models showed that Black individuals had significantly higher Aβ42 (β = 0.098, p = 0.0014); no difference was observed for p‐tau217 or p‐tau217/Aβ42 (both p≥0.43) (Figure 1). A Race X Aβ PET SUVR interaction confirmed this difference for plasma Aβ42 (β = ‐0.44, p = 0.00051; Figure 2). Conclusion Findings indicate plasma p‐tau217 levels do not differ by race, while plasma Aβ42/Aβ40 was higher in Black individuals even after accounting for differences in Aβ PET SUVR and ADI. Future work will test biomarkers in a larger sample, and examine the influence of comorbidities on differences in plasma levels and accuracy.

Background There is an urgent need for accurately predicting amyloid‐beta (Aβ) pathology in Alzheimer’s disease (AD) using non‐invasive and readily available methods, particularly in the early stages of the disease. While blood‐based biomarkers have shown promising consistency with brain Aβ pathology, there remains a scarcity of data predicting Aβ pathology using these biomarkers across different clinical settings in the Chinese population. Method We retrospectively selected 278 participants from five hospitals across China, comprising 127 patients with mild cognitive impairment (MCI) and 151 with dementia. All participants underwent amyloid PET scanning, cerebrospinal fluid (CSF) tests, and plasma analysis for Aβ42/40 ratios, phosphorylated tau181 (p‐tau181), neurofilament light chain (NfL), and APOE ε4 genotype, alongside cognitive assessments using the MMSE and MoCA. Patients were categorized as Aβ positivity based on amyloid PET or CSF Aβ42/40 ratio results, with 171 classified as Aβ positivity. Predictive models were constructed using the Random Forest algorithm for feature selection and model building. Participants were divided into a training set (n = 223) and a testing set (n = 55) for model development and validation, respectively. Result Two models were developed to differentiate Aβ positive from Aβ negative patients. The high‐accuracy model, incorporating plasma p‐tau181, plasma Aβ42/40 ratios, APOE ε4 status, MMSE, and MoCA, demonstrated excellent predictive capability with an area under the receiver‐operating characteristic curve (AUC) of 0.93 (95% CI 0.86–0.99) (Figure 1). A more parsimonious model including only plasma p‐tau181, MMSE, and MoCA also showed high accuracy (AUC: 0.86 [95% CI 0.77–0.96]) (Figure 2) in identifying patients with Aβ positivity. Both models were validated across participating centers and outperformed individual plasma biomarkers. Additionally, these models exhibited similar performance among participants with or without comorbidities or populations that included cognitively normal individuals. Conclusion The developed models, utilizing plasma biomarkers and clinically accessible parameters, provide a non‐invasive, cost‐effective approach for predicting brain amyloid positivity in the early stages of AD. This approach has potential to enhance early screening, clinical diagnosis, and the initiation of disease‐modifying therapies within the Chinese context.

Background Increased white matter hyperintensity volume (WMH) visible on MRI is a common finding in Alzheimer’s disease (AD) and is often attributed to small vessel ischemic changes. We hypothesized that WMH in preclinical AD is associated with worsening of vessel amyloidosis manifested as microhemorrhages (mH, ARIA‐H). We examine this hypothesis using cross‐sectional and longitudinal data over 4.5 years from the Anti‐Amyloid Treatment in Asymptomatic Alzheimer’s study (A4). Method MRI data from N = 1208 older adults were available at baseline (Table 1). MRI data from 1112 participants were available longitudinally (number of sessions = 5945). We extracted WMH using HyperMapper (https://hypermapp3r.readthedocs.io/). Definite mH were identified by experienced radiologists at Mayo Clinic. We categorized mH based on presence (no/yes) and by amount (level: 0, 1‐4, 4+). Linear regression compared WMH at baseline with respect to mH presence and level. We then assessed the relationships between longitudinal WMH accumulation (obtained from a linear mixed effect model) and last visit mH. Lastly, we assessed the relationship between baseline WMH and emergence of mH during follow up using a logistic regression model. All models were corrected for age, sex, grey matter volume, composite cortical amyloid PET, and APOE e4 status. Result Baseline WMH volume was greater in individuals with baseline mH compared to those without (t = 4.3, p<0.001). The longitudinal increase in WMH amongst individuals with mH at last visit was estimated to be 141 mm3/year greater than those without mH (t = 3.5, p<0.001). Both baseline and longitudinal effects were greater in individuals with more than four mH (Figure 1). Moreover, we observed that higher baseline WMH and APOE e4 status were independently related to emergence of mH during longitudinal follow‐up in A4 participants who did not have mH at baseline (Table 2). Conclusion These results suggest a strong link between WMH and ARIA‐H manifested as mH. Notably, baseline WMH was related to future mH emergence in people with no mH at baseline. This suggests increased WMH volume may represent an early sign of vessel amyloidosis, preceding the emergence of mH and thus useful in AD anti‐amyloid treatment planning.

Background We aimed to investigate the loss of synaptic density in early‐onset and late‐onset Alzheimer's Disease. Method One hundred and eighty‐two participants underwent synaptic density PET with 18F‐SynVesT‐1. Including 23 early‐onset Alzheimer‘s Disease (EOAD), 58 late‐onset Alzheimer's Disease (LOAD), 16 EOnonAD, 28 LOnonAD, 31 younger normal control (age < 65) and 26 older normal control (age ⩾ 65). We analyzed the synaptic density loss in EOAD and LOAD relative to their control group respectively. Associations between age and synaptic loss were evaluated in different groups. Result EOAD and LOAD groups both displayed significant synaptic density across most areas of cerebrum cortex. Relative to LOAD group, EOAD group showed severer synaptic loss in Lateral Parietal lobe. In EOAD group, synaptic density in occipital lobe had positive association with age. While, in LOAD group, synaptic density in most areas of the cerebrum cortex had a negative association with age. Conclusion Our study suggested that the areas of synaptic loss were different between EOAD and LOAD.

Background Among the different phospho‐tau sites, phosphorylation at Threonine 205 (pTau205) in CSF has been shown to be closely associated with Tau‐PET (Lantero‐Rodriguez et al. 2024; Barthélemy et al. 2023). Plasma brain‐derived tau (BD‐tau) has been shown to be an improved marker for amyloid‐associated neurodegeneration (Gonzalez‐Ortiz et al., 2024) compared to total tau since this reflects tau from CNS origin only. We aimed to develop prototype LUMIPULSE G assays for quantification of BD‐tau and pTau205 in EDTA plasma, to ultimately determine different biological stages of Alzheimer’s disease (AD). Method Prototype assays were developed using commercial mAbs to capture pTau205 and BD‐tau, respectively, combined with an alkaline phosphatase‐conjugated Fab fragment digested from ADx N‐terminal recombinant mAb RD‐073. Assay intra‐ and inter‐run precision, and freeze‐thaw (F/T) stability were determined. Assays were tested in an exploratory cohort using EDTA plasma samples from 50 AD patients (defined by CSF biomarker profile) and 50 healthy donors from the Dutch Brain Research Registry (Hersenonderzoek.nl). Result Levels of pTau205 and BD‐tau were within the measuring range in both control [pTau205: 0.019‐0.087 pg/mL; BD‐tau: 1.8‐6.5 pg/mL] and AD cohorts [pTau205: 0.029‐0.31 pg/mL; BD‐tau: 2.2‐20.7 pg/mL] with 100 µL undiluted and 8‐fold diluted EDTA plasma. Both assays demonstrated robust inter‐ and intra‐run precision below 15% CV. No change in concentration was observed for both analytes for up to 5 F/T cycles. The assays demonstrated moderate clinical performance in this cohort with an AUC of 0.65 [95% CI 0.54‐0.76] for pTau205 and 0.70 [95% CI 0.60 – 0.80] for BD‐tau. Both assays correlated significantly with pTau181 measured with a Quanterix Homebrew Simoa assay [pTau205: Spearman r 0.46; p<0.0001; BD‐tau: Spearman r 063; p<0.0001]. Conclusion Prototype LUMIPULSE G plasma assays for pTau205 and BD‐tau were developed using specific capture mAbs combined with an N‐terminal pan‐tau detector. The assays could measure both biomarkers in all samples from a clinical plasma cohort comprising 50 controls and 50 CSF‐biomarker confirmed AD patients. Further exploration in larger cohorts, including those characterized by Tau‐PET and Braak staging, is warranted to see whether these plasma markers provide extra information over the AD stages.

Background Effective treatments are now available, which have demonstrated reductions in amyloid plaque burden while slowing cognitive decline in early symptomatic Alzheimer’s disease (AD). Intervening before onset of cognitive impairment could provide greater benefit, particularly for individuals who carry an autosomal dominant mutation known to cause AD. To better guide the design of upcoming prevention trials, reliable sample size estimates for detecting relevant reductions in pathology are needed. Method Longitudinal PIB PET and CSF biomarker data were obtained from the Dominantly Inherited Alzheimer Network Observation study (datafreeze 14, see Table). Participants were included in the analysis based on eligibility criteria from DIAN‐TU‐001: estimated years to expected onset (EYO) between ‐15 to +10 and global Clinical Dementia Rating (CDR) score between 0 and 1, inclusive. Sample size estimates were also obtained for trials with individuals having CDR = 0 only. Linear mixed‐effects models were used to estimate baseline values and rates of change in outcome measures for mutation carriers and non‐carriers. Outcomes included CSF biomarkers of amyloid and p‐tau 181 using three assays (INNOTEST, XMAP and Lumipulse) and Standardized Uptake Value Ratio (SUVR, cerebellar grey matter reference region) of PIB PET from six regions. We then used these estimates to compute sample size estimates to detect a 25% reduction in pathology by four years, assuming 5% significance, 80% power, and 40% dropout. Uncertainty in sample size estimates was quantified through bootstrapping. Result There were large differences between carriers and non‐carriers at baseline and the end of a four‐year study (Figure 1). Sample size estimates were consistently higher in scenarios involving only CDR = 0 carriers (Figure 2). For PIB PET cortical mean, 40[95%CI: 26,66] pariticpants per arm would be needed to detect a 25% reduction and (63[40,115] for the CDR = 0 subsample. Similar estimates were observed for individual brain regions. XMAP Aβ42 (CDR 0‐1: 21, [11,65], CDR 0: 51 [21,333]) and Lumipulse Aβ42‐40 ratio (CDR 0‐1: 22 [13,46], CDR 0: 47[25,104]) were the most promising CSF outcome measures. Conclusion Sample size estimates needed to detect a 25% reduction in pathology levels in prevention studies are in the range of 30‐40 participants per arm.

Background XPro1595 (XProTM) is a brain‐penetrant, recombinant protein variant of human tumor necrosis factor (TNF) rationally designed to selectively neutralize only the soluble, pro‐inflammatory form of the cytokine (solTNF). An unbiased proteomic analysis of CSF samples from an open‐label, phase‐1b study (NCT03943264) in patients with Alzheimer’s disease (AD) was conducted to assess for pharmacodynamic activity and disease‐specific target engagement. Method Patients with AD (n = 20) were treated for 12‐weeks with one of three doses of XProTM: 0.3 (n = 5), 0.6 (n = 6) or 1.0 mg/kg/wk (n = 9). Tandem‐mass tag mass spectrometry (TMT‐MS) proteomics was performed on CSF, with lysates from three postmortem AD brains (Braak Stage IV‐VI) as control samples. Protein levels were recorded as Log2 ratios (sample/reference), with two‐sided t‐tests for determination of significant change from baseline. Differential abundance (Metascape and SynGO) and proteomic pathway (STRING) analyses were used to identify gene ontology (GO) biological processes (GOBPs) and interrelated clusters dose‐dependently affected by treatment. Due to the small sample size and exploratory nature of the study, the threshold for determination of informative values was set at P<0.05 (nominal), with no correction for multiple comparisons. Result CSF samples from fourteen patients were available for analysis: 0.3 (n = 4), 0.6 (n = 5), and 1.0 mg/kg/wk (n = 5). In total, 29,607 peptides associated with 3,632 distinct protein groups were quantified in all samples. CSF levels of 221 proteins significantly increased (n = 111) or decreased (n = 116) after treatment with the 1.0 mg/kg/wk dose of XProTM (Figure 1). GOBP and STRING pathway analyses showed high enrichment for synaptic proteins (24%) and identified a protein‐protein interaction (PPI) network of 41 proteins affected by treatment in a dose‐related manner (Figure 2). Analysis of baseline levels by PPI group (decreased or increased) showed positive within‐group intercorrelations (r > 0.535, P<0.05), with similarly negative correlations across the two groups, thus confirming interrelatedness in this sample (Figure 3A). Thirty‐two (78%) of the PPI proteins were also found to be differentially expressed in AD (Figure 3B). Conclusion Synaptic dysfunction is associated with both the clinical symptoms and core pathologies of AD. These findings provide further evidence of disease‐specific and dose‐related target engagement for XProTM in AD.