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Background AD is defined by cortical amyloid‐β (Aβ), tau neurofibrillary tangles, and neurodegeneration, pathological processes which may contribute to cognitive decline by altering large scale functional brain networks. To test this hypothesis, we examined whether plasma biomarkers of AD pathology (Aβ42/40, phosphorylated tau [pTau‐181]), astrogliosis (glial fibrillary acidic protein [GFAP]), and neuronal injury (neurofilament light chain [NfL]) related to longitudinal changes in resting‐state functional connectivity (rsFC) in cognitively unimpaired participants from the Baltimore Longitudinal Study of Aging. Method Baseline plasma biomarkers were measured with Quanterix SIMOA assays. Functional connectivity (3T resting‐state fMRI) was derived using a predefined cortical parcellation mask from which intra‐network connectivity from seven functional networks was extracted for each participant. Amyloid status (positive/negative) was defined using plasma Aβ42/40 (Figure 1). Linear mixed effects models adjusted for age, sex, race, education, gray matter volume, and time‐covariate interactions were used to determine whether 1) baseline plasma biomarkers predicted longitudinal changes in rsFC, 2) the magnitude of the biomarker‐related rsFC changes differed by amyloid status, and 3) rsFC predicted longitudinal changes in cognition. Result Longitudinal connectivity analyses (mean age±SD=65.49±16.17) included 490 participants (1190 visits; mean follow‐up time=4.31±1.68 years). Higher Aβ42/40, GFAP, and NfL were associated with faster declines in rsFC within several networks (P‐range=0.01‐0.04; Figure 2). Overall, plasma biomarker‐rsFC associations differed by amyloid status (P‐range=0.01‐0.045). Among amyloid‐positive participants, lower levels of Aβ42/40, and higher levels of GFAP, and NfL (Figure 2) were associated with faster declines in rsFC in the visual, dorsal and ventral attention, limbic, and frontoparietal networks (P range=<0.002‐0.04). There were no statistically significant associations between plasma biomarkers and rsFC change among amyloid‐negative participants. Among 760 participants with at least one rsFC scan (mean age±SD=67.21±14.93; 1550 visits, follow‐up time=3.94±1.60 years), we found that baseline rsFC in several networks predicted changes in cognition, e.g., working memory, verbal fluency, and visuospatial abilities (P range=0.02‐0.049; Figure 3). Conclusion Among cognitively normal individuals, plasma biomarkers of Aβ42/40, astrogliosis, and neuronal injury are associated with future intra‐network functional brain changes, particularly in the context of elevated amyloid. Hypo‐ and hyper‐ intra‐network connectivity may drive changes in cognitive performance.

Background Adverse social exposome (indexed by high national Area Deprivation Index [ADI]) is linked to structural inequities and increased risk of clinical dementia diagnosis, yet linkage to ADRD neuropathology remains largely unknown. Early work from single site brain banks suggests a relationship, but assessment in large national cohorts is needed to increase generalizability and depth, particularly for rarer neuropathology findings. Objective Determine the association between adverse social exposome by ADI and ADRD neuropathology for brain donors from 21 Alzheimer’s Disease Research Center (ADRC) brain banks as part of the on‐going Neighborhoods Study. Methods All brain donors in participating sites with neuropathology data deposited at the National Alzheimer’s Coordinating Center (NACC) and identifiers for ADI linkage (N = 8,637; Figure 1) were included. Geocoded donor addresses were linked to time‐concordant national ADI percentiles for year of death, categorized into standard groupings of low (ADI 1‐19), medium (20‐49) and high (50‐100) ADI. Neuropathological findings were drawn from NACC and reflected standard assessment practices at time of donation. Logistic regression models, adjusted for sex and age at death, assessed relationships between high ADI and neuropathology findings. Results Of the N = 8,637 brain donors (Table 1), 2,071 of 2,366 assessed (88%) had AD pathology by NIA‐AA criteria; 4,197 of 6,929 assessed (61%) had cerebral amyloid angiopathy; 2582 of 8092 assessed (32%) had Lewy body pathology; 391 of 2351 assessed (17%) had non‐AD tauopathy; and 586 of 1680 assessed (35%) had TDP‐43 pathology. 2,126(25%) were high ADI; 3,171(37%) medium ADI and 3,340(38%) low ADI with 51% female and average age at death of 81.9 years. As compared to low ADI donors, high ADI brain donors had adjusted odds = 1.35 (95% CI = 0.98‐1.86, p‐value = 0.06) for AD pathology; 1.10 (0.98–1.25, p = 0.11) for cerebral amyloid angiopathy; 1.37 (1.21–1.55, p<0.01) for Lewy body; 1.09 (0.83–1.44, p = 0.53) for non‐AD tauopathy; and 1.40 (1.08‐1.81, p = 0.01) for TDP‐43 pathology (Table 2). Conclusions This first‐in‐field study provides evidence that the adverse social exposome (high ADI) is strongly associated with an increased risk of Lewy body, an increased risk of TDP‐43, and a trend towards increased AD pathology in a national cohort of brain donors.

Background As blood‐based biomarkers become critical to Alzheimer’s Disease (AD) clinical testing, establishment of less invasive plasma collection methods are key. We compared the Tasso+ and the TAPII capillary whole blood collection devices to traditional venipuncture for safety and efficacy in our clinic and measured AD biomarkers neurofilament‐light (NFL), glial fibrillary acidic protein (GFAP), phosphorylated‐tau 217 (ptau217), and amyloid‐beta 42/40 ratio (Aβ42/40) in cerebrospinal fluid (CSF), capillary, and venous plasma to assess potential age and cognition related group differences. Method Patients seen at the Johns Hopkins Center for CSF Disorders (N = 193) underwent diagnostic lumbar punctures and/or extended lumbar drainage procedures. After CSF and venous plasma was collected, warming packs were held to the patient’s upper arm site for 5 minutes before capillary blood was collected via TAPII or Tasso+ device for 5 minutes. Post processing, CSF, venous, and capillary plasma was analyzed using Quanterix SIMOA immunoassays. Clinical Dementia Ratings and Montreal Cognitive Assessment scores were also collected. Result 86 TAPII and 121 Tasso+ plasma samples were collected from patients (78 M, 115 F) with mean age 61 years ± 18.3 (range 16‐91 years). The mean volume for Tasso+ samples was 294.1uL±127.2 and 266.94uL±18.71 for TAPII though this difference was not statistically significant. Tasso+ devices were 90.3% successful in collecting >50uL whole blood, and TAPII devices were 86% successful. NFL, GFAP, and Aβ42/40 ratio in CSF demonstrated moderate positive correlations with both venous and capillary plasma, although TASSO+ samples showed stronger correlation with venous plasma than TAPII (NFL Tasso r = 0.93, p<0.001, TAP r = 0.85, p<0.001; GFAP Tasso r = 0.9, p<0.001, TAP r = 0.85, p<0.001; Aβ42/40 Tasso r = 0.72, p<0.001, TAP r = 0.86, p<0.001). Ptau217 CSF measurements showed a weaker positive correlation with venous and capillary samples (Venous r = 0.34, p<0.001, Tasso r = 0.19, p = 0.048, TAP 0.05, p = 0.623). Conclusion Neurodegenerative biomarkers measured in capillary plasma as collected by the Tasso+ and TAPII correlated well with similar measures obtained from venous plasma. Tasso+ and TAPII devices performed similarly regarding success rate and volume collected.

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 In Parkinson’s disease (PD), concomitant Alzheimer’s disease (AD) pathologic change (ADNC) is common and results in altered motor and cognitive phenotypes. However, detection of PD with AD (PD+AD) using biofluid markers is challenging. While decreased cerebrospinal fluid (CSF) β‐amyloid 1‐42 (Aβ42) strongly reflects β‐amyloid burden, PD subjects typically harbor lower CSF phosphorylated tau 181 (p‐tau181) and total tau (t‐tau) levels than healthy controls, which complicates detection of tau tangles and neurodegeneration. We previously tested PD‐specific application of the β‐amyloid/tau/neurodegeneration framework (ATNPD); combining CSF Aβ42, CSF p‐tau181, and serum neurofilament light (NfL) in a living PD cohort. ATNPD, using a lower CSF p‐tau181 cutpoint, predicted cognitive decline. However, ATNPD cutpoints still must be validated against autopsy assessments of ADNC as gold‐standard. Here, we compare biomarker strategies in all available autopsy‐confirmed PD from the Parkinson’s Progression Markers Initiative (PPMI). Methods Eighteen PD participants with autopsy‐confirmed Lewy body disease and antemortem biofluid were available for analysis (Table 1). PD+AD included high/intermediate ADNC (n=9); PD without AD (PD; n=9) included not/low ADNC. Cerebral cortical atrophy determined neurodegeneration (mild/moderate vs. none). CSF was assayed for Aβ42 (n=14), p‐tau181 (n=17), and t‐tau (n=17) using Roche cobas e 601; p‐tau181/Aβ42 and t‐tau181/Aβ42 ratios were calculated. Serum NfL was assayed using Simoa Quanterix (n=18). Biofluid measurements closest to autopsy were selected. Receiver operating characteristic (ROC) analyses with bootstrapping tested discrimination of PD+AD from PD using CSF biomarkers, and of neurodegeneration from not using CSF t‐tau and serum NfL. Results ROC cutpoints for CSF Aβ42, p‐tau181, and serum NfL were equivalent to ATNPD cutpoints, while p‐tau181 and t‐tau were lower than published AD‐cutpoints (Table 2). CSF p‐tau181/Aβ42, t‐tau181/Aβ42, Aβ42 and serum NfL had high area under the curve (AUC>0.80; Table 2A,2B). In contrast, CSF p‐tau181 and t‐tau demonstrated poor discrimination (Table 2A) and no difference between groups (Table 1), potentially due in part to low sample size. A chi‐square test confirmed classification is improved using ATNPD and AD‐cutpoints (χ2=14, p=0.0015; Figure 1). Conclusions PD‐specific biomarker strategies/cutpoints are needed to maximize detection of concomitant ADNC, but must be validated in larger autopsy cohorts.

Background Previous studies have suggested a correlation between elevated levels of β2‐microglobulin (B2M) and cognitive impairment. However, the existing evidence is insufficient to establish a conclusive relationship. This study aims to analyse the link of plasma B2M to cerebrospinal fluid (CSF) Alzheimer's Disease (AD) biomarkers, and cognition. Method To track the dynamics of plasma B2M in preclinical AD, 846 cognitively healthy individuals in the Chinese Alzheimer's Biomarker and LifestylE (CABLE) cohort were divided into four groups (suspected non‐AD pathology [SNAP], 2, 1, 0) according to NIA‐AA criteria. Multiple linear regression models were employed to examine plasma B2M’s relationship with cognitive and CSF AD biomarkers. Causal mediation analysis was conducted through 10,000 bootstrapped iterations to explore the mediating effect of AD pathology on cognition. Result We found that the levels of plasma B2M were increased in stages 1 (P=0.0007) and 2 (P< 0.0001), in contrast to stage 0. In total participants, higher levels of B2M were associated with worse cognitive performance (P = 0.006 for MMSE; P= 0.012 for MoCA). Moreover, a higher level of B2M was associated with decreases in Aβ1‐42 (P<0.001) and Aβ1‐42/Aβ1‐40 (P=0.015) as well as increases in T‐tau/Aβ1‐42 (P<0.001) and P‐tau/Aβ1‐42 (P<0.001). Subgroup analysis found B2M correlated with Aβ1‐42 in non‐APOE ε4 individuals (P<0.001) but not in APOE ε4 carriers. Additionally, the link between B2M and cognition was partially mediated by Aβ pathology (percentage: 8.6% to 19.3%), whereas tau pathology did not mediate this effect. Conclusion This study consolidated demonstrated the association of plasma B2M with CSF AD biomarkers as well as a possible important role of Aβ pathology in the association between B2M and cognitive impairment, particularly in cognitively normal individuals, particularly in cognitively normal individuals. The results indicated that B2M could be a potential biomarker for preclinical AD and might have varied functions throughout various stages of preclinical AD progression.

Background C‐reactive protein (CRP) and growth differentiation factor 15 (GDF15) are important markers of inflammation associated with several aging‐related morbidities. DNA methylation (DNAm) measures of CRP and GDF15 may provide stable epigenetic measures of chronic exposure to inflammation and could therefore be robustly predictive of inflammation‐related brain aging and neurodegeneration. Methods Data from a subsample of cognitively normal older adults (n = 431) from the Baltimore Longitudinal Study of Aging with DNA methylation (DNAm) data and longitudinal structural neuroimaging (up to 8 visits, 16.4 years) were used. We used latent growth curve models (Mplus 8.2) to explore the effect of two DNAm signatures (DNAm‐GDF15 and DNAm‐CRP) on longitudinal trajectories of 17 brain region volumes. These included total brain, total lobar, total lobar white matter, and other regions vulnerable to AD‐pathology. Results Our analyses revealed several brain regions in which level (at age 75) and change were significantly predicted by DNAm‐GDF15 and DNAm‐CRP (Table 1). Specifically, higher DNAm‐GDF15 predicted lower volumes and greater decline in the total brain (βi = ‐11.93; βs = ‐0.40), total grey matter (βi = ‐6.25; βs = ‐0.23), and total white matter regions (βi = ‐8.35; βs = ‐0.35), as well as greater ventricular volume and increases (βi = 4.62; βs = 0.35). Our analyses also revealed broad effects of GDF15 on total lobar, total lobar white matter, and AD‐specific regions. Our second set of conditional growth models revealed that higher DNAm‐CRP predicted lower volumes and greater decline in the total brain (βi = ‐4.30; βs = ‐0.23) and total white matter regions (βi = ‐4.58; βs = ‐0.19), as well as greater ventricular volume and increases (βi = 3.58; βs = 0.19). DNAm‐CRP also broadly predicted level and decline in volume for several total lobar and total lobar white matter regions, but these effects did not extend to AD‐specific regions. Conclusions In a sample of cognitively normal older adults, epigenetic signatures representing longer‐term exposure to two inflammatory proteins differentially predicted brain volume trajectories. Notably, DNAm measures of GDF15 showed particularly strong associations with a broader breadth of brain regions as compared to DNAm‐CRP.

Background Identification of useful fluid biomarkers is expected to advance frontotemporal dementia spectrum disorders (FTD) care and therapeutic development. The clinical utility of emerging plasma Amyloid, Tau, and Neurodegeneration (ATN) biomarkers in FTD remains unexplored. This study analyzed ATN patterns by sporadic FTD phenotype, based on amyloid beta1‐42 (Aβ1‐42), amyloid beta1‐40 (Aβ1‐40), phospho‐tau217 (p‐tau217), and neurofilament (NfL) plasma concentrations. Method The present study included 625 participants enrolled in ALLFTD (46% female, median age 61 ± 12 years) for whom biomarker data were available. Plasma Aβ1‐42/Aβ1‐40 measures were determined by immunoprecipitation‐mass spectrometry whereas plasma p‐tau217 and NfL concentrations were respectively determined by electrochemiluminescence‐ and fluorescence‐based immunoassays. Biomarker concentrations were compared by phenotype and disease severity with ANOVA. Their diagnostic performance was tested with Receiver Operating Characteristic (ROC) curves, and biomarker relationships with measures of clinical severity were tested through linear regressions controlling for age, sex, and APOE genotype. Result Higher plasma p‐tau217 and p‐tau217/Aβ1‐42, levels were observed in logopenic primary progressive aphasia (lvPPA) and amnestic dementia (AmD) cohorts, compared to other FTD groups. These biomarkers were not associated with disease severity but were affected by APOE4 genotype. High plasma NfL level was observed in fully symptomatic patients compared to controls, and as a function of disease severity. Plasma Aβ1‐42/Aβ1‐40 level was not different between phenotypes and was not affected by clinical severity. P‐tau217 level, but not Aβ1‐42/Aβ1‐40 or NfL levels showed high discrimination of lvPPA and AmD from other phenotypes (AUC = 0.87 (95% CI 0.77 – 0.96, p < 0.0001, 73% sensitivity, 92% specificity). The p‐tau217/Aβ1‐42 ratio improved this discrimination (AUC = 0.9, 95% CI 0.83 – 1, p < 0.0001, 77% sensitivity, 94% specificity). Plasma Aβ1‐42/Aβ1‐40, p‐tau217, NfL, p‐tau217/Aβ1‐42, p‐tau217/NfL, and (Aβ1‐42 x p‐tau217)/NfL were associated with cognitive (MoCA, CVLT), motor (UPDRS), and social behavior (RSMS) performances at baseline. Conclusion Plasma p‐tau217/Aβ1‐42 identifies, with high specificity, two phenotypes associated with Alzheimer’s disease: lvPPA and AmD. Pending molecular neuroimaging and neuropathological confirmation, this biomarker could be of value to identify primary Alzheimer’s disease pathology or co‐pathology associated with Alzheimer’s disease when sporadic FTD is suspected.