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Abstract Background Chronic kidney disease (CKD) is associated with increased blood‐based biomarker concentrations, potentially confounding their utility in Alzheimer's disease (AD) evaluation. While plasma phosphorylated tau217 ( p ‐tau217) is elevated in the presence of amyloid related pathology, amyloid beta 1‐42 (Aβ42) is decreased. We investigated the association of plasma p ‐tau217, non‐phosphorylated tau217 (np‐tau217), Aβ42, Aβ40, as well as the Aβ42/Aβ40 and p ‐tau217/Aβ42 ratios, versus decreased estimated glomerular filtration rate (eGFR in mL/min/1.73 m 2 ) in individuals without amyloid pathology. Method This study included participants with CKD stages 1‐2 (eGFR 60‐98, n = 50), and stages 3‐4 (eGFR 25‐59, n = 33), who were Pittsburgh 11 C‐Compound B amyloid‐PET negative (Centiloid of < 25). Plasma p ‐tau217, np‐tau217, Aβ42, and Aβ40 were measured by immunoprecipitation mass spectrometry (C 2 N Diagnostics). %p‐tau217 [( p ‐tau217/np‐tau217) x100], Aβ42/Aβ40 ratio, and p ‐tau217/Aβ42 ratio were calculated. Log‐Log (power function) best‐fit regression analysis was used to quantitatively predict effects of changes in eGFR (2021 CKD‐EPI equation) versus each single analyte or ratio (Figure 1). Result Selected best‐fit analyte equations versus eGFR are shown in Table 1. The predicted percent increase of p ‐tau217 as eGFR decreases from 60 to 45 was 52% (95% CI: 30–78%). Significantly smaller increases of 16% were predicted for Aβ42 (95% CI: 12–21%), and 19% for Aβ40 (95% CI: 16–23%) over the same eGFR range. The best‐fit predicted increase for the p ‐tau217/Aβ42 ratio and %p‐tau217 as eGFR decreases from 60 to 45 was 31% (95% CI: 12–53%), and 19% (95% CI: 2–38%), respectively. While not recommended for assessment of amyloid pathology, the Aβ42/Aβ40 ratio did not exhibit a predicted increase (‐2.3% decrease, 95% CI: ‐5.2–0.6%) versus decreasing eGFR from 60 to 45. Conclusion The use of either %p‐tau217 or the p ‐tau217/Aβ42 ratio (to a lesser degree) reduced the confounding effects of decreasing eGFR as compared to p ‐tau217 alone. Aβ42 and Aβ40 exhibited similar reduced predicted increases versus decreasing eGFR as compared to p ‐tau217. Relative to the predicted effects of decreasing eGFR on p ‐tau217 measurements, the p ‐tau217/Aβ42 ratio relative increase was reduced by 40%, while the relative increase was reduced by 63% for %p‐tau217 measurements.

Abstract Background Self‐administered and remote digital cognitive assessments provide a scalable method for screening and longitudinal cognitive monitoring. Mayo Test Drive (MTD) is one such assessment with previously demonstrated usability, reliability, validity and multi‐device compatibility. MTD includes a computer‐adaptive word list memory test (Stricker Learning Span) and a measure of processing speed/executive functioning (Symbols Test) that combine to provide an MTD Composite. This study aimed to develop a conditional normative model predicting longitudinal cognitive change for MTD, and to validate the model in two independent samples of cognitively unimpaired (CU) and mild cognitive impairment (MCI)/dementia (DEM) participants. Method 1355 CU participants at initial MTD assessment with 2‐4 consecutive MTD assessments every 7.5 months comprised the development dataset. Linear mixed effects models were used to construct a conditional normative model for MTD assessments 2‐4. The baseline model was chosen a priori , consisting of age, sex, education, baseline score, number of assessments, and time. Device type, race, and baseline score by time interactions were also considered. Variables were only added if a >1% increment in r‐squared was observed. The models were externally validated in 113 CU and 51 MCI/DEM patients. Following model development, the data were updated and additional follow‐up MTD assessments were added for many participants, including the addition of additional CU validation data at test 3 ( N = 126) and 4 ( N = 279). T‐tests compared observed and predicted differences and residual z‐scores between development and validation at each follow‐up assessment. Result Table 1 presents demographic variables. No additional variables increased the r‐squared by >1%. The final models are presented in Table 2. Age, baseline score, sex, and education were significant. Residual z‐scores were not significantly different between CU development and CU validation cohorts, indicating observed scores were in line with model predicted scores. Residual z‐scores were significantly worse among MCI/DEM compared to CU development in 11/12 comparisons (Figure 1), indicating observed scores were below model predicted expectations and implying sensitivity to longitudinal cognitive decline. Conclusion These longitudinal normative models can be used to identify individuals with follow‐up scores outside of expected predicted ranges, signifying abnormal longitudinal cognitive decline.

Abstract Background In addition to visuospatial and visuoperceptual deficits, most PCA patients also report deficits in visual attention, episodic memory, and working memory. The dorsal attention network is known to play a critical role in modulating these clinical functions. However, little is known about the relationship of the dorsal attention network with other core networks and relationships to volume loss and memory functions in PCA. Method Fifty‐seven PCA patients were recruited by the Neurodegenerative Research group, Mayo Clinic, and compared to 60 cognitively unimpaired (CU) individuals from the Mayo Clinic Study of Aging. The CONN functional connectivity toolbox was used to calculate within‐ and between‐network connectivity. Functional connectivity within the key regions (i.e., inter‐hemisphere connectivity) of the dorsal attention network, namely frontal eye field (FEF) and intraparietal sulcus (IPS), and the entire network was generated. Functional connectivity between the dorsal attention network and the frontoparietal, visual, and default mode networks (DMN) were also generated using CONN's network parcellation atlas. Multivariate linear regression models were fit i) to compare within‐ and between‐network connectivity between both groups and ii) to assess relationships between within‐network connectivity and both gray matter volumes and clinical test scores. Result PCA showed reduced within‐network connectivity in the dorsal attention network, specifically within the IPS and the entire network compared to CU. An increase in between‐network connectivity between the frontoparietal network and both FEF and the entire dorsal attention network was noted in PCA compared to CU (Figure 1). Lower dorsal attention within‐network connectivity was associated with a trend for lower volumes in the entire network (Figure 2) and significantly lower scores on the auditory verbal learning test‐recognition percent correct (AVLT‐RCP) and Wechsler Memory Scale (WMS) III‐digit span backward in PCA (Figure 3). Conclusion These findings suggest that within‐ and between‐network connectivity of the dorsal attention network, both within key regions and the entire network, was disrupted in PCA patients. However, this network did not show disrupted connectivity with the core PCA networks. Within‐network connectivity disruptions in the dorsal attention network are associated with aspects of memory function, and to some extent, with volume loss.

Abstract Background Alzheimer's disease (AD) exhibits significant genetic heterogeneity, with no single model fully explaining its inheritance pattern. Structural variants (SVs) may contribute to the missing heritability of AD, particularly in disease pathology and familial AD, which remain largely unexplored. Method Structural variants (SVs) were analyzed in unrelated 1,162 individuals from the ROSMAP study (687 cognitively normal (CN), 475 AD patients), as well as 197 Non‐Hispanic White (NHW) families (926 individuals, 58.5% with AD) and 214 Caribbean Hispanic (CH) families (1,340 individuals, 59.17% with AD). Large insertions and deletions were identified using Manta, Absinthe, and MELT from whole‐genome sequencing, supplemented by Sniffles2 and external SV call sets. This approach generated a unified VCF file containing 45,251 insertions and 76,566 deletions. After filtering for missingness rate and allele counts, a total of 9,290 insertions and 9,529 deletions were retained for analysis. Genome‐wide SV analyses were performed with AD‐related metrics in ROSMAP, adjusting for age, sex, and principal components, and validated in an independent ADSP replication cohort comprising 29,055 unrelated individuals (17,110 CN and 11,945 AD patients). Result We identified nine SVs (one insertion and eight deletions) segregating in AD families. An insertion near PDCD10 in NHW families reached genome‐wide significance ( p <5×10 ‐8 ) for AD risk in the replication cohort. Two deletions in KIF26B and SPHKAP were found in both CH and NHW families, while five appeared only in NHW and one in CH. All eight deletions showed genome‐wide significance for AD risk. SV GWAS on AD pathologies in ROSMAP revealed an insertion in INPP4B with the strongest association to global brain pathology (β=0.19; p = 2.32×10 ‐5 ), also linked to pathological AD, diffuse plaques, and Braak staging. A deletion near ADGRB1 (β=1.53; p = 5.05×10 ‐6 ) was associated with neuritic plaques, and another near ARMC2 (β=1.66; p = 2.17×10 ‐6 ) was linked to diffuse plaques. All three SVs associated with AD ( p <5×10 ‐6 ) in replication. Conclusion Our findings reveal numerous SVs segregating in familial AD across both CH and NHW families, as well as additional SVs linked to sporadic AD. Prioritizing these SVs based on their potential effects on gene function and expression will provide deeper insight into their contributions to both familial and sporadic AD.

Abstract Background Monoclonal antibodies targeting amyloid‐β (Aβ), including aducanumab, have been tested to treat Alzheimer's disease (AD). However, limited data exist on neuropathology following treatment and the effects of amyloid‐related imaging abnormalities (ARIA). We report on such data from five aducanumab‐treated study participants with AD of whom two experienced ARIA. Methods Aducanumab‐treated study participants who came to autopsy ( n = 5) were matched to AD controls ( n = 12) based on the presence/type of autosomal dominant AD mutation, APOE genotype, age at cognitive symptom onset, and sex. We assessed cognitive measures, 18 F‐florbetapir PET centiloid, ARIA risk factors, and AD neuropathologic change. Using multiplex immunofluorescence, brain regions affected along Thal Aβ phases were stained for Aβ isoforms and phosphorylated tau, as well as for ARIA‐associated markers, including Perls’ Prussian blue to detect ferric iron, fibrinogen‐α for blood brain barrier integrity, membrane attack complex (C5b‐C9) for complement activation, and activated microglia (IBA1, CD68). Results Study participants included four males and one female, all carrying at least one APOE ε4 allele. Two participants carried a PSEN1 NM_000021.4:c.817G>A , p.Glu273Lys mutation. Cumulative aducanumab dosage ranged between 5–241 mg/kg, with death occurring 5–41 months after the last infusion. Amyloid burden on PET declined in all participants (range 15‐100 centiloids). Two participants experienced ARIA. Compared to AD controls, Aβ aa1‐8 and Aβ 42 were selectively reduced in cortical layer I of aducanumab‐treated study participants ( p <0.05) but not in the total cortex, as shown for the middle frontal cortex in Figure 1. No differences were observed in phosphorylated tau burden. Prussian blue‐stained hemosiderin was present in both treated and untreated AD cases. However, in participants with ARIA, hemosiderin accumulated in superficial cortical layers near CAA‐laden meningeal and penetrating vessels, which also exhibited extensive complement and microglial activation (Figure 2). Conclusions Aβ clearance and ARIA‐related findings were localized predominantly in superficial cortical layers, suggesting that aducanumab biodistribution is more pronounced in these regions rather than deeper cortical layers.

Abstract Background Aging and dementia are generally associated with lower metabolism in gray matter on FDG‐PET and have been widely studied. However, white matter (WM) metabolic changes remain understudied. We investigated the metabolic changes in WM associated with aging and dementia and their relationships with established Alzheimer's Disease (AD) biomarkers and cognitive outcomes. Method We analyzed data from 3,169 participants (72 ± 9 years; 53% male; 65% cognitively unimpaired) enrolled in the Mayo Clinic Study of Aging (MCSA) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). All participants underwent baseline MRI, amyloid‐PET, and FDG‐PET scans, as well as neuropsychological evaluations, with at least one clinical follow‐up. Voxel‐wise multiple regression analysis identified WM metabolic changes associated with global cognition in cognitively unimpaired MCSA participants ( n = 1,754). Univariate analyses and structural equation models were applied to elucidate the driving factors underlying the WM metabolic changes in MCSA data. Multiple regression and linear mixed‐effects models evaluated the explanatory utility of WM metabolism for baseline global cognition and cognitive decline in both cohorts. In a subset of MCSA participants, we evaluated neurite density index from diffusion MRI as a surrogate of WM health and glial fibrillary acidic protein (GFAP) as a surrogate of neuroinflammation to understand underlying mechanisms. Result We identified an atypical WM signature (AWM‐Signature) in the anterior and superior corona radiata, where glucose metabolism increased as cognitive performance worsened (Figure 1). Hypermetabolism in AWM‐Signature was related to increased age, amyloidosis, vascular disease, and neuroinflammation, as well as decreasing WM neurite density in the same regions (Figure 2). Hypermetabolism in AWM‐Signature regions predicted faster future cognitive decline, even after accounting for demographics, amyloid, and vascular disease metrics. The results observed in the AWM‐Signature regions were consistently in the opposite direction of the associations seen with gray matter and typical WM regions. Conclusion We found unexpected metabolism increases in corona radiata, a hub that carries significant portion of the brain's neural traffic, with aging and disease which likely indicates a compensatory response. These changes may be useful cognitive resilience measures and require further investigation to understand their role in maintaining cognitive function.

Abstract Background Chronic disease conditions lead to brain changes elevating dementia risk. We hypothesized that tissue microstructural changes caused by type 2 diabetes mellitus (T2DM) and hypertension could be effectively captured using an advanced diffusion MRI technique, Neurite Orientation Dispersion and Density Imaging (NODDI). Our goal was to evaluate the usefulness of composite NODDI scores, customized for increased hemoglobin (Hb) A1c and systolic blood pressure as predictors of cognition and compare their performance to other measures typically used to assess dementia risk. Method We collected multi‐shell diffusion MR on 1024 Mayo Clinic Study of Aging participants. NODDI measures (neurite density index (NDI), orientation dispersion index (ODI), and free water fraction (FWF)) in gray matter (GM) and white matter (WM) regions were estimated. To identify brain regions susceptible to both conditions, a multiple linear regression model was fitted for each NODDI metric, using hemoglobin (Hb) A1c (in N = 305 participants) or systolic blood pressure ( N = 906) as predictor, with age, sex, and body mass index (BMI) as covariates. Event‐based modeling was performed with the identified NODDI metrics to investigate the chronological pattern along the course of chronic condition development from this cross‐sectional dataset. Composite metrics were created as a weighted sum of susceptible NODDI metrics. We evaluated the impact of both conditions on cognition using gradient boosting models incorporating composite metrics, additional brain measurements, and demographics. Result Increased HbA1c impacts both GM and WM NODDI relatively evenly, whereas increased systolic blood pressure related NODDI changes were mainly seen in WM (data not shown). With increased HbA1c, the earliest changes were observed in GM ODI, followed by changes in the pons and cortical FWF (Figure 1A). With increased systolic blood pressure, the earliest changes occurred in association fibers and middle cerebellar peduncle, followed by FWF change in lobar and projection WM fibers (Figure 1B). Average feature importance from 100 gradient boosting models for cognition prediction suggests that diabetes‐induced GM changes play a moderately important role in cognitive decline (Figure 2). Conclusion Chronic medical conditions, especially T2DM, result in brain changes that are captured by NODDI and contribute moderately to cognitive performance.

Abstract Background Clinically available plasma p ‐tau217 assays may be utilized in the determination of eligibility for amyloid‐lowering therapies. Our institution recently introduced a plasma p ‐tau217 assay in clinical practice using a two‐cutpoint approach that optimizes the accuracy while minimizing false positive risk and categorizing ≤20% of results as intermediate. In this study, we prospectively evaluate the performance of a plasma p ‐tau217 assay for detection of amyloid pathology using these predefined cutpoints. Method Patients recruited were being considered for lecanemab therapy at a tertiary care subspecialty clinic. Plasma p ‐tau217 was measured using the clinically available Fujirebio Lumipulse p ‐tau217 assay at Mayo Clinic, and results (pg/mL) were classified as either negative (≤0.185), intermediate (0.186–0.324) or positive (≥0.325). Amyloid pathology was determined by amyloid‐PET and/or CSF p ‐tau181/Aβ42. Result Ninety‐three patients were recruited between November 2023 and December 2024. Of these, 49 underwent amyloid‐PET, 4 had CSF p ‐tau181/Aβ42 measurements, and 40 had both PET and CSF results (with 3/40 discordant cases), for use in the assessment of amyloid pathology. The three discordant cases were considered amyloid positive for purposes of plasma p ‐tau217 comparison. Overall amyloid positivity was 90%. Plasma p ‐tau217 results were positive in 83% (77/93), negative in 6% (6/93), and intermediate in 11% (10/93) of patients. An elevated p ‐tau217 predicted the presence of amyloid positivity with a diagnostic accuracy of 96% (95% CI 90% − 99%). In the intermediate range, 80% of patients were positive for amyloid pathology. In patients with a definitive p ‐tau217 result (positive or negative), the positive and negative predictive values were 97% and 83%. There were three patients with discordant results: one PET+/p‐tau217‐, one PET‐/p‐tau217+, and one CSF‐/p‐tau217+. Clinical presentation of these discordant cases was examined, and relevant findings will be discussed. Conclusion The Lumipulse plasma p ‐tau217 assay exhibited acceptable diagnostic accuracy for the determination of amyloid pathology when compared to either amyloid‐PET or CSF p ‐tau181/Aβ42. This prospective study confirms the utility a two‐cutpoint approach for interpreting plasma p ‐tau217 for the assessment of amyloid pathology eligibility for amyloid‐lowering therapies in a heterogenous clinical cohort.

Abstract Background Cerebral amyloid angiopathy (CAA), characterized by the accumulation of amyloid‐beta in the cerebrovasculature, affects blood vessel integrity leading to brain hemorrhages and an accelerated cognitive decline in Alzheimer's Disease (AD) patients. Our previous genome‐wide association study (GWAS) identified a LINC‐PINT splice variant associated with lower CAA levels in individuals without the APOE e4 allele and higher levels of LINC‐PINT expression in the brain of AD donors. In this study, we expand our GWAS to include additional donors with AD and those lacking significant AD neuropathology (non‐AD), with available CAA scores. Method In our prior study we assessed 853 AD donors. We expanded this by addition of genetic data from 550 AD and 502 non‐AD donors from the Mayo Clinic Brain Bank, scored for CAA. We performed QC and imputation (TOPMED) of all datasets. We conducted GWAS in AD only ( N = 1,363), non‐AD only, and all donors ( N = 1,865) by testing imputed variant dosages for association with square root transformed CAA using linear regression, adjusting for relevant covariates. To assess associations in the context of major CAA risk factors, we performed interaction analysis with APOEe4 presence and sex; and pursued stratified analyses. Result Variants at the APOE locus were identified as the most significant in our study. In addition, several other variants approached genome‐wide significance after adjusting for AD neuropathology (Braak stage and Thal phase). The LINC‐PINT splice variant remained associated with lower CAA scores in AD donors without the APOEe4 risk allele . To enhance the robustness of our findings, we are pursuing further expansion of our study cohort to include other available datasets. To explore putative functional consequences of key variants we are collecting peripheral gene expression measures in participants from Mayo Clinic with neuroimaging measures including microhemorrhages. Conclusion We expect this study will provide further insights into the genetic architecture underlying risk for CAA, both in the context of significant AD pathology, and without. Characterization of genetic variants and their functional outcomes may lead to new avenues of research aimed at identifying biomarkers and therapies to treat CAA, a common co‐pathology in those with and without AD.

Abstract Background Individuals with coexisting Alzheimer's disease (AD) and disorders of CSF dynamics such as normal‐pressure hydrocephalus (NPH) have lower CSF Aβ42 levels, which can confound interpretation of AD CSF‐biomarkers. However, little is known about how CSF dynamics influences plasma AD biomarkers. The objective of this study was to determine whether mass spectrometry‐based blood tests for AD are associated with disproportionately enlarged subarachnoid space hydrocephalus (DESH) on MRI. Method 509 Individuals from the Mayo Clinic Study of Aging, with MRI, 11C‐Pittsburgh compound B (Aβ) PET scans, and plasma phosphorylated‐tau protein 217, Aβ40 and Aβ42 were included. We performed an age‐adjusted logistic regression to determine whether abnormal values of p ‐Tau 217 (Abnormal if >1.55 pg/mL), %p‐tau217 defined as the ratio of phosphorylated Tau217 to non‐phosphorylated tau x 100% (Abnormal if >1.55%), Aβ42 (Abnormal if <41.5 pg/mL), and Aβ42/40 ratio (Abnormal if <0.094) were associated with the presence of DESH, as classified by a previously validated automated algorithm. Result Thirty‐two participants were classified as DESH‐positive. The median [IQR] age was 76.8 yrs [70.6, 82.9] for participants with DESH and 72.4 [59.3, 85.5] without DESH (Table 1). An abnormal plasma Aβ42 was associated with DESH (OR, 2.56 [1.19, 5.74], p = 0.018), but having an abnormal Aβ42/40 ratio (OR 2.01 [0.94, 4.56], p = 0.079) was not. There was no association between being DESH‐positive and an abnormal plasma p ‐tau217 (OR 1.30 [0.51, 3.09], p = 0.560) or with abnormal %plasma p ‐tau217 (OR 1.82 [0.74, 4.20], p = 0.17) (Figure 1). Subgroup analysis showed that only those participants who had an abnormal Aβ42 and positive amyloid PET (≥25 Centiloids) showed an association with DESH compared to biomarker‐ and PET‐negative participants (OR 3.10 [1.15, 8.43], p = 0.024 ) . Conclusion Understanding how CSF dynamics affect plasma biomarkers is critical for implementation. The relationship between lower Aβ42 and DESH is expected based on prior CSF studies, which can be addressed by using an amyloid ratio. p ‐tau217 shows robustness against DESH, making it a suitable biomarker in cases of abnormal cerebrospinal fluid dynamics although validation in a more severe CSF dynamics group is warranted.