Jack, Clifford R.

Background: Periodontal disease (PD) is associated positively with neurocognitive outcomes. Few studies have investigated the relationship between PD and indicators of brain aging and vascular changes. Hypothesis: PD is associated with greater cerebral small vessel disease, lower total and regional brain volumes and elevated β-amyloid (Aβ) deposition. Methods: We included 6,793 participants who received full-mouth periodontal examinations and tooth counts at Visit 4 (1996-1998) of the Atherosclerosis Risk in Communities Study. We used a modified 3-level version of the Periodontal Profile Class to categorize PD based on severity and extent of gingival inflammation and tissue loss. Among participants who attended Visit 5 (2011-2013), n=1,306 received a brain MRI and n=248 received a PET scan. Total brain volume, Alzheimer’s disease signature volume, and presence of microhemorrhages and cerebral infarctions were ascertained via 3T MRI; Aβ deposition was assessed from PET. We regressed brain volumes on baseline PD status using weighted multivariable linear regression. Presence of cerebrovascular microhemorrhages, infarctions, or elevated Aβ (standardized uptake value ratio>1.2) were regressed on PD category using logistic models. We examined the interaction between Apolipoprotein E ε4 ( APOE ) allele possession and PD categories on the Aβ outcome. Results: Prevalence of baseline periodontal disease was 73% (959/1306) and 87% (206/248) among the MRI and PET subgroups, respectively. PD was not associated with volumetric brain measures nor microhemorrhages. PD was inversely associated with the odds of subcortical and lacunar infarctions. PD and Aβ were not associated in main effect or interaction analyses, although there was a notably stronger association among carriers of APOE . Conclusion: PD was not associated with altered brain structure, cerebral microhemorrhages or elevated Aβ deposition. Counter to the hypothesis, PD and complete tooth loss were inversely associated with cerebral infarctions.

Introduction: Studies have found that smaller brain volumes, cerebral infarcts, and white matter abnormalities are associated with dementia and mild cognitive impairment. However, these studies have been limited by short follow-up precluding a strong establishment of temporality. Therefore, it is unknown whether brain imaging findings are preceded by long-term changes in cognition. We sought to address this gap by examining brain imaging and two decades of cognitive changes in and a large, representative population-based cohort of older adults of black and white race. Hypothesis: We hypothesized that 22-year declines in global cognitive factor scores (GCFS) would be associated with a pattern of smaller total brain and temporal lobe meta region of interest (likely to be affected by Alzheimer’s disease) volumes, larger white matter hyperintensity volumes, and greater odds of ≥1 lacunar infarct and elevated brain β-amyloid deposition. Methods: ARIC participants with brain imaging data, complete cognitive factor score, and not missing key covariates were included. GCFS were collected at three visits across 22 years (1990-2013), and brain MRI and florbetapir PET imaging were collected in 2011-13; PET in subset of n=327. Mixed effects models with random intercepts and slopes predicted individual change in GCFS. Outcomes of interest were total brain volume (cc), temporal lobe meta region volume, log 2 (white matter hyperintensity volume), ≥1 lacunar infarct, and elevated brain β-amyloid deposition (SUVR >1.2). Multivariable linear and logistic regression was used to relate outcomes to GCFS slopes after adjusting for confounders, including vascular risk factors. As appropriate, models were also adjusted for total intracranial volume. Results: Among 1957 with complete brain MRI imaging, 1830 were included in the study, 60% (n=1096) women and 26% (n=480) black. At the first visit, the mean (SD) baseline age was 55 (5.2) yrs. The mean (SD) observed GCFS at the three visits were 0.16 (0.79), 0.05 (0.75), and -0.78 (0.86). After adjustment, a 1-SD larger decline in GCFS was significantly associated with a smaller brain volume by 1.6% [95%CI: 1.3, 1.8] relative to mean brain volume, a smaller temporal lobe meta region volume by 2.4% [2.1, 2.8] relative to the mean volume, a 15% [11, 19] larger volume of white matter hyperintensities, 1.3-fold [1.2, 1.4] higher odds of having ≥1 lacune, and 1.8-fold [1.4, 2.4] higher odds of elevated brain β-amyloid deposition. Associations remained significant after further adjustment for first or last GCFS. Conclusions: Greater declines in long-term cognitive functioning were significantly associated with smaller brain volumes and dementia-related brain characteristics and were independent of last visit GCFS. This suggests long-term changes in cognition may precede late-life brain morphology and outperform cross-sectional cognitive measures.

Background: Elevated carotid intima-media thickness (cIMT) and presence of carotid plaque are markers of atherosclerosis, which may be linked to structural brain injury. Using data from the ARIC-NCS cohort, we tested the hypotheses that greater cIMT and presence of carotid plaque at late midlife were each associated with presence of infarcts (lacunar and cortical) and cerebral microbleeds (lobar and subcortical), greater white matter hyperintensity (WMH) volume, and smaller regional brain volumes in late life. Methods: We included 1,795 ARIC participants who had carotid ultrasounds in 1990-92 and brain MRI scans in 2011-13. Weighted linear regression was used for continuous (brain volume) outcomes, and weighted logistic regression for dichotomous outcomes (infarcts and cerebral microbleeds). Results: Participants were aged 57±6 years at baseline, 57% were female, and 23% were Black. Mean ± SD follow-up was 21±1 years. After multivariable adjustments, the highest quintile of cIMT in late midlife was associated with smaller deep grey matter volume (β [95% CI]: -0.11 [-0.22, -0.01]) and cortical volume in a temporal-parietal meta region of interest (ROI) (β [95% CI]: -0.10 [-0.20, -0.01]) in late life (Table). At baseline, 473 (26%) participants had carotid plaque present on their carotid ultrasound. Similar to cIMT, those with carotid plaque had smaller regional brain volumes than those without carotid plaque present (βs [95% CIs]: -0.05 [-0.12, 0.03] and -0.06 [-0.13, 0.01] for deep grey matter and temporal-parietal meta ROI volumes, respectively). No significant relations were observed with WMH volume, or the presence of any infarcts or cerebral microbleeds. Conclusion: Greater midlife cIMT and presence of carotid plaque were associated with smaller deep grey matter volume and cortical volume in a temporal-parietal meta ROI in later life. Contrary to our hypothesis, associations between midlife subclinical atherosclerosis and markers of vascular brain injury in later life were null.

Abstract Introduction Measurement of amyloid beta (Aβ40 and Aβ42) and tau (phosphorylated tau [p‐tau] and total tau [t‐tau]) in cerebrospinal fluid (CSF) can be utilized to differentiate clinical and preclinical Alzheimer's disease dementia (AD) from other neurodegenerative processes. Methods CSF biomarkers were measured in 150 participants from the Mayo Clinic Study of Aging and the Alzheimer's Disease Research Center. P‐tau/Aβ42 (Roche Elecsys, Fujirebio LUMIPULSE) and Aβ42/40 (Fujirebio LUMIPULSE) ratios were compared to one another and to amyloid positron emission tomography (PET) classification. Results Strong correlation was observed between LUMIPULSE p‐tau/Aβ42 and Aβ42/40, as well as Elecsys and LUMIPULSE p‐tau/Aβ42 and Aβ42/40 (Spearman's ρ = –0.827, –0.858, and 0.960, respectively). Concordance between LUMIPULSE p‐tau/Aβ42 and Aβ42/40 was 96% and between Elecsys p‐tau/Aβ42 and both LUMIPULSE ratios was 97%. All ratios had > 94% overall, positive, and negative percent agreement with amyloid PET classification. Discussion These data suggest that p‐tau/Aβ42 and Aβ42/40 ratios provide similar clinical information in the assessment of amyloid pathology.

Abstract Introduction: Biomarkers that reflect pathologic processes affecting neuronal function during preclinical and early stages of Alzheimer's disease (AD) are needed to aid drug development. Methods: A targeted, stable isotope, quantitative mass spectrometry‐based investigation of longitudinal changes in concentrations of previously identified candidate biomarkers was performed in cerebrospinal fluid (CSF) of Alzheimer's Disease Neuroimaging Initiative participants who were classified as cognitively normal (CN; n = 76) or with mild cognitive impairment (MCI; n = 111) at baseline. Results: Of the candidate biomarkers, the CSF concentration of neuronal pentraxin 2 (NPTX2), a protein involved in synaptic function, exhibited rates of change that were significantly different between three comparison groups (i.e., CN vs. MCI participants; AD pathology positive vs. negative defined by phosphorylated tau181/amyloid beta1‐42 ratio; and clinical progressors vs. non‐progressors). The rate of change of NPTX2 also significantly correlated with declining cognition. Discussion: CSF NPTX2 concentration is a strong prognostic biomarker candidate of accelerated cognitive decline with potential use as a therapeutic target.

Introduction: We recently reported that abnormal P-wave indices (PWI)—ECG markers of atrial cardiomyopathy (AC)—are associated with an increased risk of dementia, independent of atrial fibrillation (AF) and clinical ischemic stroke. The mechanisms, however, remain unclear, but may include silent ischemia. Hypothesis: Abnormal PWI are associated with higher prevalence of cortical infarcts on MRI, suggesting cardioembolism as a potential mechanism. Methods: ARIC-NCS participants (mean age, 72.2±5.3 years; 60% women; 29% black) who underwent 3T brain MRI scans in 2011-2013 were included. Abnormal PWI included P-wave terminal force in lead V1 [(PTFV1) defined as ≥4000 μV*ms] and P-wave duration [(PWD) defined as >120 ms], which were measured from standard 12-lead ECGs. Brain MRI outcomes included cortical infarcts, cerebral microbleeds (CMB), and markers of small vessel disease [white matter hyperintensities (WMH) and lacunar infarcts]. We used weighted multivariable logistic and linear regression analyses. Results: Of the 1,850 participants, 464 had abnormal PTFV1 and 415 had prolonged PWD. After multivariable adjustment including AF, abnormal PTFV1 and PWD were significantly associated with 26-44% increased odds of cortical and lacunar infarcts (Table) . Although PWD was associated with CMB in Model 1, the association was no longer significant after multivariable adjustment. Finally, abnormal PWIs were not associated with WMH after adjusting for stroke and AF (P >0.5). Conclusions: Abnormal PWI are associated with higher prevalence of cortical infarcts, suggesting cardioembolism with silent ischemia as a possible mechanism underlying the association of AC with dementia. More research is needed to evaluate other mechanisms such as cerebral small vessel disease.

Background and Purpose: Cerebral microbleeds (CMBs) are represented by small areas of hemosiderin deposition, detected on brain magnetic resonance imaging (MRI), and found in ≈23% of the cognitively normal population over age of 60 years. CMBs predict risk of hemorrhagic and ischemic stroke. They correlate with increased cardiovascular mortality. In this article, we sought to determine in a population-based study whether antithrombotic medications correlate with CMBs and, if present, whether the association was direct or mediated by another variable. Methods: The study consisted of 1253 participants from the population-based Mayo Clinic Study of Aging who underwent T2* gradient-recalled echo magnetic resonance imaging. We tested the relationship between antithrombotic medications and CMB presence and location, using multivariable logistic-regression models. Ordinal logistic models tested the relationship between antithrombotics and CMB frequency. Using structural equation models, we assessed the effect of antithrombotic medications on presence/absence of CMBs and count of CMBs in the CMB-positive group, after considering the effects of age, sex, vascular risk factors, amyloid load by positron emission tomography, and apoE. Results: Two hundred ninety-five participants (26.3%) had CMBs. Among 678 participants taking only antiplatelet medications, 185 (27.3%) had CMBs. Among 95 participants taking only an anticoagulant, 43 (45.3%) had CMBs. Among 44 participants taking an anticoagulant and antiplatelet therapy, 21 (48.8%) had CMBs. Anticoagulants correlated with the presence and frequency of CMBs, whereas antiplatelet agents were not. Structural equation models showed that predictors for presence/absence of CMBs included older age at magnetic resonance imaging, male sex, and anticoagulant use. Predictors of CMB count in the CMB-positive group were male sex and amyloid load. Conclusions: Anticoagulant use correlated with presence of CMBs in the general population. Amyloid positron emission tomography correlated with the count of CMBs in the CMB-positive group.

Purpose A standard MRI system phantom has been designed and fabricated to assess scanner performance, stability, comparability and assess the accuracy of quantitative relaxation time imaging. The phantom is unique in having traceability to the International System of Units, a high level of precision, and monitoring by a national metrology institute. Here, we describe the phantom design, construction, imaging protocols, and measurement of geometric distortion, resolution, slice profile, signal‐to‐noise ratio (SNR), proton‐spin relaxation times, image uniformity and proton density. Methods The system phantom, designed by the International Society of Magnetic Resonance in Medicine ad hoc committee on Standards for Quantitative MR, is a 200 mm spherical structure that contains a 57‐element fiducial array; two relaxation time arrays; a proton density/SNR array; resolution and slice‐profile insets. Standard imaging protocols are presented, which provide rapid assessment of geometric distortion, image uniformity, T 1 and T 2 mapping, image resolution, slice profile, and SNR. Results Fiducial array analysis gives assessment of intrinsic geometric distortions, which can vary considerably between scanners and correction techniques. This analysis also measures scanner/coil image uniformity, spatial calibration accuracy, and local volume distortion. An advanced resolution analysis gives both scanner and protocol contributions. SNR analysis gives both temporal and spatial contributions. Conclusions A standard system phantom is useful for characterization of scanner performance, monitoring a scanner over time, and to compare different scanners. This type of calibration structure is useful for quality assurance, benchmarking quantitative MRI protocols, and to transition MRI from a qualitative imaging technique to a precise metrology with documented accuracy and uncertainty.

Abstract While cerebrovascular disease can be observed in vivo using MRI, the multiplicity and heterogeneity in the mechanisms of cerebrovascular damage impede accounting for these measures in ageing and dementia studies. Our primary goal was to investigate the key sources of variability across MRI markers of cerebrovascular disease and evaluate their impact in comparison to amyloidosis on cognitive decline in a population-based sample. Our secondary goal was to evaluate the prognostic utility of a cerebrovascular summary measure from all markers. We included both visible lesions seen on MRI (white matter hyperintensities, cortical and subcortical infarctions, lobar and deep microbleeds) and early white matter damage due to systemic vascular health using diffusion changes in the genu of the corpus callosum. We identified 1089 individuals aged ≥60 years with concurrent amyloid-PET and MRI scans from the population-based Mayo Clinic Study of Aging. We divided these into discovery and validation datasets. Using the discovery dataset, we conducted principal component analyses and ascertained the main sources of variability in cerebrovascular disease markers. Using linear regression and mixed effect models, we evaluated the utility of these principal components and combinations of these components for the prediction of cognitive performance along with amyloidosis. Our main findings were (i) there were three primary sources of variability among the CVD measures—white matter changes are driven by white matter hyperintensities and diffusion changes; number of microbleeds (lobar and deep); and number of infarctions (cortical and subcortical); (ii) Components of white matter changes and microbleeds but not infarctions significantly predicted cognition trajectories in all domains with greater contributions from white matter; and (iii) The summary vascular score explained 3–5% of variability in baseline global cognition in comparison to 3–6% variability explained by amyloidosis. Across all cognitive domains, the vascular summary score had the least impact on memory performance (∼1%). Though there is mechanistic heterogeneity in the cerebrovascular disease markers measured on MRI, these changes can be grouped into three components and together explain variability in cognitive performance equivalent to the impact of amyloidosis on cognition. White matter changes represent dynamic ongoing damage, predicts future cognitive decline across all domains and diffusion measurements help capture white matter damage due to systemic vascular changes. Therefore, measuring and accounting for white matter changes using diffusion MRI and white matter hyperintensities along with microbleeds will allow us to capture vascular contributions to cognitive impairment and dementia.

BackgroundTo operationalize the National Institute on Aging – Alzheimer's Association (NIA‐AA) Research Framework for Alzheimer's Disease 6‐stage continuum of clinical progression for persons with abnormal amyloid.MethodsThe Mayo Clinic Study of Aging is a population‐based longitudinal study of aging and cognitive impairment in Olmsted County, Minnesota. We evaluated persons without dementia having 3 consecutive clinical visits. Measures for cross‐sectional categories included objective cognitive impairment (OBJ) and function (FXN). Measures for change included subjective cognitive impairment (SCD), objective cognitive change (ΔOBJ), and new onset of neurobehavioral symptoms (ΔNBS). We calculated frequencies of the stages using different cutoff points and assessed stability of the stages over 15 months.ResultsAmong 243 abnormal amyloid participants, the frequencies of the stages varied with age: 66 to 90% were classified as stage 1 at age 50 but at age 80, 24 to 36% were stage 1, 32 to 47% were stage 2, 18 to 27% were stage 3, 1 to 3% were stage 4 to 6, and 3 to 9% were indeterminate. Most stage 2 participants were classified as stage 2 because of abnormal ΔOBJ only (44–59%), whereas 11 to 21% had SCD only, and 9 to 13% had ΔNBS only. Short‐term stability varied by stage and OBJ cutoff points but the most notable changes were seen in stage 2 with 38 to 63% remaining stable, 4 to 13% worsening, and 24 to 41% improving (moving to stage 1).InterpretationThe frequency of the stages varied by age and the precise membership fluctuated by the parameters used to define the stages. The staging framework may require revisions before it can be adopted for clinical trials. ANN NEUROL 2021;89:1145–1156