Citations

Abstract Impaired kidney function is a risk factor for cognitive decline and dementia, but most studies use serum creatinine-based equations to estimate kidney function as estimated glomerular filtration rate (eGFR); these equations include age, also a strong driver of cognitive impairment, and produce eGFR estimates with substantial error compared to gold-standard objective measures of GFR (mGFR). The purpose of this study was to determine eGFR and mGFR associations with cognitive function in African American adults, a population disproportionately impacted by both chronic kidney disease and dementia. We conducted a cross-temporal analysis of 368 participants (Age: 66.4 ± 7.4y, 75% Female) in the Genetic Epidemiology Network of Arteriopathy study with eGFR (CKD-EPI 2021 Creatinine Race-Free Equation) and mGFR assessed. eGFR was assessed using the CKD-EPI 2021 Creatinine Race-Free Equation and mGFR (urinary clearance of non-radiolabeled iothalamate). Memory (Rey Auditory Verbal Learning Test; RAVLT) and executive function (Digit Symbol Substitution Test; DSST) were assessed. Linear regression models were used to relate eGFR, mGFR, and serum creatinine to cognitive function with and without adjustment for age and sex. In unadjusted models, eGFR was positively associated with DSST scores (β = 0.19, 95%CI:0.11, 0.27) and RAVLT scores (β = 0.10, 95%CI:0.04, 0.16). mGFR was marginally associated with DSST scores (β = 0.07, 95%CI:-0.00, 0.14), but not RAVLT scores (β = 0.03, 95%CI:-0.01, 0.07). Associations of serum creatinine with cognitive function were mostly null to marginal. Age and sex adjustment greatly attenuated all associations. The observed differential renal function associations with cognition suggest age may largely explain prior reported associations.

Abstract Lower cerebral perfusion is associated with adverse outcomes, but risk factors are poorly understood. This study examined associations of cumulative systolic blood pressure [SBP], diabetes, and BMI from mid- to late-life with late-life cerebral perfusion, using whole-brain MRI Arterial Spin Labeling (ASL). Cumulative exposures were defined as either average continuous SBP or BMI across visits or number of years with diabetes, hypertension, or obesity. Multiple regression, adjusted for age and gender, estimated ASL (β: 95% CI) among participants without prevalent conditions at baseline in participants with ASL data from the Atherosclerosis Risk in Communities Study (ARIC; Jackson, MS; n = 100; age=81±3 years; 65% Female; 100% Black participants; 34 years retrospective risk factor assessments (1987-2021); pulsed ASL, 8/2021-1/2024) and the Mayo Clinic Study of Aging (MCSA; Rochester, MN; n = 537; age=71±13 years; 36.3% Female, 100% White participants; 18 years retrospective risk factor assessments (2005-2023); pseudo-continuous ASL 2/2023-3/2024). A 10 mmHg higher cumulative SBP was associated with a 0.04 lower ASL (MCSA β=-0.04; -0.01, -0.07; ARIC β=-0.04; -0.09, 0.01). A 10 kg/m2 higher cumulative BMI was associated with a 0.30 lower ASL (-0.51, -0.08) in ARIC and 0.03 lower ASL (-0.16, 0.10) in MCSA participants. Every five additional years of diabetes exposure was associated with a 0.03 (-0.06, -0.01) lower ASL in ARIC and 0.11 (-0.27, 0.05) lower ASL in MCSA participants. High BP, obesity, and diabetes may contribute to poor cerebral perfusion over extended exposures from midlife. Longer risk factor assessment periods and different ASL techniques may explain differences in the cohorts.

Abstract Background Prospective investigations on blood biomarkers for Alzheimer's disease and related‐dementias (ADRDs) and cognitive impairment provide important insights into their clinical utility in early disease diagnosis and risk stratification, but have been primarily limited to AD pathologies (e.g. amyloid‐beta and hyperphosphorylated‐tau aggregation). Studies of biomarkers reflecting other pathogenic processes that contribute to ADRDs, especially in community‐based cohorts, are lacking. We examined associations of blood biomarkers reflecting glial and neuronal dysfunction and neuroinflammation, including soluble cluster of differentiation‐14 (sCD14), chitinase‐3‐like protein‐1 (YKL‐40), glial‐fibrillary acidic protein (GFAP), neurofilament‐light chain (NfL), total‐Tau, and Ubiquitin C‐terminal hydrolase L1 (UCH‐L1) with cognitive decline and incident dementia in ARIC study participants. Methods Blood biomarkers were measured in 1,864 ARIC Visit 3 (1993‐1995) participants using the Meso Scale Discovery assay (YKL‐40), the Quanterix Simoa Neurology 4‐Plex assay (total‐Tau, NfL, GFAP, UCH‐L1), and a commercial ELISA assay (sCD14, R&D Systems); global cognition z‐scores were derived from three cognitive tests (measuring memory, language, and executive function) administered up to six times over 25 years, and incident dementia cases were ascertained via in‐person cognitive assessments (expert‐adjudicated), informant‐based interviews, and hospitalization and death records through 2018. We used shared parameter models to simultaneously fit linear mixed‐effect models and proportional hazard models to estimate 25‐year cognitive decline and dementia rates separately for each biomarker (log‐base2‐transformed), adjusting for covariates (Table). Results Among 1,864 participants (mean±SD age:63±4.5 years, 60% female, 49% self‐reported Black), 27% developed dementia. Higher levels of each biomarker were associated with faster cognitive decline. All but UCH‐L1 were associated with elevated dementia risk (Table). For example, one standard deviation (SD) higher log‐base2 YKL‐40 was associated with ‐0.10 SD steeper 25‐year cognitive decline (95%CI:‐0.15,‐0.04) and 59% higher dementia hazard (hazard ratio (HR):1.59 (95%CI:1.20,2.10); likewise, sCD14 was associated with an additional cognitive decline of ‐0.06 (95%CI:‐0.11,‐0.01) and 38% higher dementia hazard (HR:1.38 (95%CI:1.08,1.76)). Conclusions Blood biomarkers reflecting neuropathological processes, including microglial activation, astrocytic reactivity, and neuronal degeneration, were associated with faster cognitive decline and increased dementia risk, suggesting that they may aid in risk stratification and intervention strategies for ADRDs. Future analyses will examine whether these associations differ by race and APOE‐ε4 s tatus.

Abstract Background Diffusion MRI (dMRI) measures are increasingly being used as biomarkers for aging and dementia in multi‐center studies. Measurements in longitudinal studies are often acquired on different systems, which can result in systematic differences of machine origin (e.g. vendor, hardware, algorithms). This may warrant harmonization prior to pooling multi‐site data. However, harmonization algorithms may introduce a risk of removing valuable information content and reducing sensitivity to physiological factors (e.g. sex, age, disease). Here, we tested the hypothesis that protocol standardization may minimize machine‐origin differences, obviating a need for post‐acquisition harmonization in a two‐site (Mississippi‐MS and Minnesota‐MN) cohort of the longitudinal Mayo Clinic Study of Aging (MCSA). Methods Two data sets were analyzed: first, a crossover dataset with 80 participants (scanned within 2 days) bridging two different protocols on GE and Siemens scanners; second, participants scanned using standardized protocols from the ongoing MCSA ( N MN‐MCSA =204; N MS‐MCSA =52). Parameters are listed in Figure 1. For crossover data, analyses were repeated with GE data resampled to 2‐mm isotropic resolution, and discarding Siemens‐only b‐shells to artificially reduce protocol disparities. Analysis encompassed visualization of overlain subjectwise histogram‐derived densities obtained from whole‐brain masks for dMRI measures; and median dMRI measures from within the genu of the corpus callosum (GCC) with nonparametric statistical testing. When available, both DTI and NODDI measures were compared. Results Pronounced visual distributional differences seen between MD and FA in crossover data were reduced with resampling of GE data and including only b‐shells shared across acquisitions. For the resampled/reshelled data, significant differences remained for all GCC‐FA comparisons, but not all GCC‐MD (Figure 2). For the ongoing MCSA data from two sites, MD and FA whole‐brain densities were more closely aligned, with GCC‐FA and GCC‐MD showing no significant differences (Figure 3). NODDI measures showed more discordant densities than DTI measures, including shifts in most probable values and differences in distributional arrangement. Conclusions Our work provides further evidence supporting protocol and processing standardization for minimizing machine‐origin differences prior to considering harmonization. Differences in dMRI metrics seen when comparing across unstandardized protocols were reduced when protocols were standardized. NODDI metrics had more apparent sensitivity to site than DTI measures.

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 A workgroup assembled by the Alzheimer’s Association recently described a conceptual framework for Alzheimer’s disease biological staging based on amyloid and tau PET imaging. However, specific tau PET cut points were left to be determined, a step necessary prior to clinical application. We sought to operationalize and evaluate Alzheimer’s disease biological staging by identifying meaningful tau PET cut points to define the four biological stages in a well-characterized participant cohort and describe the features of individuals placed into the different biological stages. The primary analysis included 896 participants in the Mayo Clinic Study of Aging or the Mayo Clinic Alzheimer’s Disease Research Center longitudinal cohorts. A validation cohort consisted of 328 participants in the Alzheimer’s Disease Neuroimaging Initiative. Both cognitively normal and impaired individuals with positive amyloid PET and evaluable tau PET imaging were included. Tau PET cut points were identified with Gaussian mixture models to characterize Alzheimer’s disease biological stage in study participants with different clinical diagnoses and objective degrees of cognitive impairment as measured by Mini-Mental State Examination. A tau PET cut point in the medial temporal region and two cut points in the temporoparietal region were identified to produce, collectively, the four Alzheimer’s disease biological stages described in the revised criteria. Increasing stage was associated with greater likelihood of mild cognitive impairment and dementia diagnosis and worsening cognitive performance on Mini-Mental State Examination and Clinical Dementia Rating Sum of Boxes, a result that was reproduced in the independent Alzheimer’s Disease Neuroimaging Initiative cohort. This study provided empirical validation for the concept of using amyloid PET and tau PET to separate subjects with biomarker-proven Alzheimer’s disease into four biological stages with distinct characteristics.

Abstract INTRODUCTION Plasma biomarkers’ utility for predicting incident mild cognitive impairment (MCI) remains unclear. We evaluated associations of plasma Alzheimer's disease (AD) biomarkers and amyloid positron emission tomography (PET) with transitions from cognitively unimpaired (CU) to MCI in the Mayo Clinic Study of Aging (MCSA) and BioFINDER‐2 studies. METHODS Associations of continuous baseline plasma biomarker levels and amyloid PET Centiloid with progression to MCI, adjusting for age, sex, and education, were evaluated with Cox proportional hazards models. RESULTS The study included 381 MCSA and 584 BioFINDER‐2 participants. Amyloid PET and percent phosphorylated to non‐phosphorylated tau217 (%p‐tau217) were strong predictors of progression to MCI in both cohorts: hazard ratios of 1.49 and 1.23 in the MCSA and 1.72 and 1.65 in BioFINDER, respectively. Amyloid beta 42/40 was a significant predictor in BioFINDER‐2 only (hazard ratio 2.20). DISCUSSION Plasma %p‐tau217 was associated with progression from CU to MCI in both cohorts, although differences in biomarker associations may be related to differences in the two cohorts. Highlights Mass‐spectrometry‐based plasma phosphorylated tau217 was associated with cognitively unimpaired to mild cognitive impairment (MCI) progression. Plasma amyloid beta 42/40 was a significant predictor in BioFINDER but not the Mayo Clinic Study of Aging (MCSA). Amyloid positron emission tomography (PET) was the strongest predictor of progression to MCI in the MCSA. Plasma had added value to amyloid PET in BioFINDER but not the MCSA. Biomarker performance may vary with cohort and biomarker measurement differences.

Abstract INTRODUCTION Limited data exist on the utility of plasma biomarkers to predict incident abnormal amyloid positron emission tomography (PET). In this study we evaluate the association of plasma Alzheimer's disease (AD) biomarkers with amyloid PET progression among initially amyloid PET negative (A−) individuals. METHODS We included 290 A−, cognitively unimpaired Mayo Clinic Study of Aging participants. We estimated the association of each baseline plasma biomarker with progression from A− to A+ and with rate of amyloid PET change. RESULTS Interquartile range differences in amyloid beta 42/40, percent phosphorylated tau 217 (%p‐tau217), and Amyloid Probability Score 2 were associated with 1.29 ( P = 0.09), 1.38 ( P < 0.001), and 1.20 ( P = 0.05) increases, respectively, in the hazard of progression from A− to A+ and 0.27 ( P = 0.16), 0.50 ( P = 0.007), and 0.28 ( P = 0.15) Centiloid/year increases, respectively, in annual rate of amyloid PET change. DISCUSSION Plasma %p‐tau217 may be a useful screening tool to enrich for participants with increased likelihood of progressing from normal to abnormal amyloid PET in a primary prevention trial. Highlights Plasma phosphorylated tau 217 was associated with amyloid positron emission tomography progression, negative to positive. The associations were weaker for amyloid beta 42/40 and Amyloid Probability Score 2. Age and apolipoprotein E ε4 carriership were also important predictors. These markers may be useful for enrichment of a primary prevention trial.