Petersen, Ronald C.

Abstract Introduction Meta-analytic studies support that insomnia is a risk factor for cognitive decline and dementia, but limited accounting of confounders reduces their validity. Further, it is unclear whether these associations are driven by specific insomnia phenotypes. In this study, we aimed to assess the relationship between insomnia and longitudinal global cognitive decline in community-dwelling older adults after considering self-reported sleep duration changes and other important characteristics. Methods From the Mayo Clinic Study of Aging (MCSA) cohort, we identified all (age>=50yo) cognitively unimpaired participants at baseline without comorbid neurological disease with at least two previous comprehensive neuropsychological evaluations. Participants with at least two occurrences of insomnia ICD diagnosis (by EMR and Rochester Epidemiological Project data) at least 30 days apart were classified as having insomnia, and those without any instance of diagnosis were considered negative for insomnia. Changes in sleep duration were assessed using the question #16 of BDI-2 and categorized in reduced sleep (yes/no). We fit mixed-effect regression models to assess whether insomnia was associated with standardized global cognitive scores, after adjusting for age, sex, education, APOEe4, composite cardiovascular and metabolic conditions scores, anxiety/depression, reduced sleep, OSA (ICD diagnosis), alcoholism (CAGE≥2), and pain (NSAIDs use). Number of cognitive assessments and time from baseline were included as both fixed and random effects. Multiple interactions (e.g. insomnia*reduced sleep) were included. A backward stepwise procedure maintaining the hierarchical principal for interactions was utilized to reach the most parsimonious models. Results 3063 participants (50.24% males, aged 70±9.73 at baseline) were included. Insomnia alone was not associated with a decrease in global cognition, but when combined with subjective reduction in sleep duration at baseline it was associated with a -0.19 (95% CI: -0.32, -0.07; interaction p=0.01) reduction in global cognitive scores. This was equivalent to approximately 3 additional years of age or 6 cardiometabolic comorbidities at baseline. The effect size was greater than those associated with baseline cognition for having any APOE e4 allele (-0.12) and alcoholism (-0.15). Conclusion Insomnia with reduced sleep duration phenotype is a potentially modifiable risk factor for cognitive decline in older adults. Further studies with objective sleep measures are necessary for objective confirmation. Support (if any) NIA/NIH

Importance Factors associated with clinical heterogeneity in Alzheimer disease (AD) lay along a continuum hypothesized to associate with tangle distribution and are relevant for understanding glial activation considerations in therapeutic advancement. Objectives To examine clinicopathologic and neuroimaging characteristics of disease heterogeneity in AD along a quantitative continuum using the corticolimbic index (CLix) to account for individuality of spatially distributed tangles found at autopsy. Design, Setting, and Participants This cross-sectional study was a retrospective medical record review performed on the Florida Autopsied Multiethnic (FLAME) cohort accessioned from 1991 to 2020. Data were analyzed from December 2022 to December 2023. Structural magnetic resonance imaging (MRI) and tau positron emission tomography (PET) were evaluated in an independent neuroimaging group. The FLAME cohort includes 2809 autopsied individuals; included in this study were neuropathologically diagnosed AD cases (FLAME-AD). A digital pathology subgroup of FLAME-AD cases was derived for glial activation analyses. Main Outcomes and Measures Clinicopathologic factors of heterogeneity that inform patient history and neuropathologic evaluation of AD; CLix score (lower, relative cortical predominance/hippocampal sparing vs higher, relative cortical sparing/limbic predominant cases); neuroimaging measures (ie, structural MRI and tau-PET). Results Of the 2809 autopsied individuals in the FLAME cohort, 1361 neuropathologically diagnosed AD cases were evaluated. A digital pathology subgroup included 60 FLAME-AD cases. The independent neuroimaging group included 93 cases. Among the 1361 FLAME-AD cases, 633 were male (47%; median [range] age at death, 81 [54-96] years) and 728 were female (53%; median [range] age at death, 81 [53-102] years). A younger symptomatic onset (Spearman ρ = 0.39, P < .001) and faster decline on the Mini-Mental State Examination (Spearman ρ = 0.27; P < .001) correlated with a lower CLix score in FLAME-AD series. Cases with a nonamnestic syndrome had lower CLix scores (median [IQR], 13 [9-18]) vs not (median [IQR], 21 [15-27]; P < .001). Hippocampal MRI volume (Spearman ρ = −0.45; P < .001) and flortaucipir tau-PET uptake in posterior cingulate and precuneus cortex (Spearman ρ = −0.74; P < .001) inversely correlated with CLix score. Although AD cases with a CLix score less than 10 had higher cortical tangle count, we found lower percentage of CD68-activated microglia/macrophage burden (median [IQR], 0.46% [0.32%-0.75%]) compared with cases with a CLix score of 10 to 30 (median [IQR], 0.75% [0.51%-0.98%]) and on par with a CLix score of 30 or greater (median [IQR], 0.40% [0.32%-0.57%]; P = .02). Conclusions and Relevance Findings show that AD heterogeneity exists along a continuum of corticolimbic tangle distribution. Reduced CD68 burden may signify an underappreciated association between tau accumulation and microglia/macrophages activation that should be considered in personalized therapy for immune dysregulation.

The immune system substantially influences age-related cognitive decline and Alzheimer’s disease (AD) progression, affected by genetic and environmental factors. In a Mayo Clinic Study of Aging cohort, we examined how risk factors like APOE genotype, age, and sex affect inflammatory molecules and AD biomarkers in cerebrospinal fluid (CSF). Among cognitively unimpaired individuals over 65 ( N = 298), we measured 365 CSF inflammatory molecules, finding age, sex, and diabetes status predominantly influencing their levels. We observed age-related correlations with AD biomarkers such as total tau, phosphorylated tau-181, neurofilament light chain (NfL), and YKL40. APOE4 was associated with lower Aβ42 and higher SNAP25 in CSF. We explored baseline variables predicting cognitive decline risk, finding age, CSF Aβ42, NfL, and REG4 to be independently correlated. Subjects with older age, lower Aβ42, higher NfL, and higher REG4 at baseline had increased cognitive impairment risk during follow-up. This suggests that assessing CSF inflammatory molecules and AD biomarkers could predict cognitive impairment risk in the elderly.

Abstract Background White matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer’s disease pathology. Their distinct spatial distributions, namely periventricular versus deep WMH, may differ by underlying age-related and pathobiological processes contributing to cognitive decline. We aimed to identify the spatial patterns of WMH using the 4-scale Fazekas visual assessment and explore their differential association with age, vascular health, Alzheimer’s imaging markers, namely amyloid and tau burden, and cognition. Because our study consisted of scans from GE and Siemens scanners with different resolutions, we also investigated inter-scanner reproducibility and combinability of WMH measurements on imaging. Methods We identified 1144 participants from the Mayo Clinic Study of Aging consisting of older adults from Olmsted County, Minnesota with available structural magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). WMH distribution patterns were assessed on FLAIR-MRI, both 2D axial and 3D, using Fazekas ratings of periventricular and deep WMH severity. We compared the association of periventricular and deep WMH scales with vascular risk factors, amyloid-PET and tau-PET standardized uptake value ratio, WMH volume, and cognition using Pearson partial correlation after adjusting for age. We also evaluated vendor compatibility and reproducibility of the Fazekas scales using intraclass correlations (ICC). Results Periventricular and deep WMH measurements showed similar correlations with age, cardiometabolic conditions score (vascular risk), and cognition, (p < 0.001). Both periventricular WMH and deep WMH showed weak associations with amyloidosis (R = 0.07, p = < 0.001), and none with tau burden. We found substantial agreement between data from the two scanners for Fazekas measurements (ICC = 0.78). The automated WMH volume had high discriminating power for identifying participants with Fazekas ≥ 2 (area under curve = 0.97). Conclusion Our study investigates risk factors underlying WMH spatial patterns and their impact on global cognition, with no discernible differences between periventricular and deep WMH. We observed minimal impact of amyloidosis on WMH severity. These findings, coupled with enhanced inter-scanner reproducibility of WMH data, suggest the combinability of inter-scanner data assessed by harmonized protocols in the context of vascular contributions to cognitive impairment and dementia biomarker research.

Abstract Senescent cell accumulation contributes to the progression of age-related disorders including Alzheimer’s disease (AD). Clinical trials evaluating senolytics, drugs that clear senescent cells, are underway, but lack standardized outcome measures. Our team recently published data from the first open-label trial to evaluate senolytics (dasatinib plus quercetin) in AD. After 12-weeks of intermittent treatment, we reported brain exposure to dasatinib, favorable safety and tolerability, and modest post-treatment changes in cerebrospinal fluid (CSF) inflammatory and AD biomarkers using commercially available assays. Herein, we present more comprehensive exploratory analyses of senolytic associated changes in AD relevant proteins, metabolites, lipids, and transcripts measured across blood, CSF, and urine. These analyses included mass spectrometry for precise quantification of amyloid beta (Aß) and tau in CSF; immunoassays to assess senescence associated secretory factors in plasma, CSF, and urine; mass spectrometry analysis of urinary metabolites and lipids in blood and CSF; and transcriptomic analyses relevant to chronic stress measured in peripheral blood cells. Levels of Aß and tau species remained stable. Targeted cytokine and chemokine analyses revealed treatment-associated increases in inflammatory plasma fractalkine and MMP-7 and CSF IL-6. Urinary metabolites remained unchanged. Modest treatment-associated lipid profile changes suggestive of decreased inflammation were observed both peripherally and centrally. Blood transcriptomic analysis indicated downregulation of inflammatory genes including FOS, FOSB, IL1β, IL8, JUN, JUNB, PTGS2. These data provide a foundation for developing standardized outcome measures across senolytic studies and indicate distinct biofluid-specific signatures that will require validation in future studies. ClinicalTrials.gov: NCT04063124.

AbstractINTRODUCTIONPatients with dementia with Lewy bodies (DLB) may have Alzheimers disease (AD) pathology that can be detected by plasma biomarkers. Our objective was to evaluate plasma biomarkers of AD and their association with positron emission tomography (PET) biomarkers of amyloid and tau deposition in the continuum of DLB, starting from prodromal stages of the disease.METHODSThe cohort included patients with isolated rapid eye movement (REM) sleep behavior disorder (iRBD), mild cognitive impairment with Lewy bodies (MCI‐LB), or DLB, with a concurrent blood draw and PET scans.RESULTSAbnormal levels of plasma glial fibrillary acidic protein (GFAP) were found at the prodromal stage of MCI‐LB in association with increased amyloid PET. Abnormal levels of plasma phosphorylated tau (p‐tau)‐181 and neurofilament light (NfL) were found at the DLB stage. Plasma p‐tau‐181 showed the highest accuracy in detecting abnormal amyloid and tau PET in patients with DLB.DISCUSSIONThe range of AD co‐pathology can be detected with plasma biomarkers in the DLB continuum, particularly with plasma p‐tau‐181 and GFAP.