Knopman, David S.

Abstract Deterioration in white-matter health plays a role in cognitive ageing. Our goal was to discern heterogeneity of white-matter tract vulnerability in ageing using longitudinal imaging data (two to five imaging and cognitive assessments per participant) from a population-based sample of 553 elderly participants (age ≥60 years). We found that different clusters (healthy white matter, fast white-matter decliners and intermediate white-matter group) were heterogeneous in the spatial distribution of white-matter integrity, systemic health and cognitive trajectories. White-matter health of specific tracts (genu of corpus callosum, posterior corona radiata and anterior internal capsule) informed about cluster assignments. Not surprisingly, brain amyloidosis was not significantly different between clusters. Clusters had differential white-matter tract vulnerability to ageing (commissural fibres > association/brainstem fibres). Identification of vulnerable white-matter tracts is a valuable approach to assessing risk for cognitive decline.

AbstractTo examine the length of a hexanucleotide expansion in C9orf72, which represents the most frequent genetic cause of frontotemporal lobar degeneration and motor neuron disease, we employed a targeted amplification-free long-read sequencing technology: No-Amp sequencing. In our cross-sectional study, we assessed cerebellar tissue from 28 well-characterized C9orf72 expansion carriers. We obtained 3507 on-target circular consensus sequencing reads, of which 814 bridged the C9orf72 repeat expansion (23%). Importantly, we observed a significant correlation between expansion sizes obtained using No-Amp sequencing and Southern blotting (P = 5.0 × 10−4). Interestingly, we also detected a significant survival advantage for individuals with smaller expansions (P = 0.004). Additionally, we uncovered that smaller expansions were significantly associated with higher levels of C9orf72 transcripts containing intron 1b (P = 0.003), poly(GP) proteins (P = 1.3 × 10− 5), and poly(GA) proteins (P = 0.005). Thorough examination of the composition of the expansion revealed that its GC content was extremely high (median: 100%) and that it was mainly composed of GGGGCC repeats (median: 96%), suggesting that expanded C9orf72 repeats are quite pure. Taken together, our findings demonstrate that No-Amp sequencing is a powerful tool that enables the discovery of relevant clinicopathological associations, highlighting the important role played by the cerebellar size of the expanded repeat in C9orf72-linked diseases.

Abstract Few studies examined race-regional influences on mild cognitive impairment (MCI) and dementia risk factors. We examined 14 risk factors in 5 race-regions, e.g. cross-sectional age- and sex-adjusted relative prevalence ratios (RPR) from multinomial regression comparing associations of low education (<12yrs) with MCI and dementia (versus normal cognition) across 3 race-region groups, average age 76yrs: whites in the Mayo Clinic Study of Aging[MCSA, Olmsted County, MN—MCSA-MN-Whites); Atherosclerosis Risk in Communities(ARIC) whites in suburban Minneapolis, MN—ARIC-MN-Whites); ARIC-African Americans in Jackson, MS—ARIC-MS-AA. Among 3,787 MCSA-Whites, low education exerted a 2-fold risk for MCI, RPR=2.09(95%CI: 1.57,2.78). Conversely, low education was not a supported MCI risk factor for ARIC-MN-Whites (n=1,901—RPR=0.63(0.31,1.28) or ARIC-MS-AA, (n=1,416—RPR=.0.81 (0.60,1.10)), with substantially differential race-region effects. Low education RPRs for dementia also differed by race-region: RPR=4.43(2.68,7.31-MCSA-MN-W), RPR=0.70 (0.16,2.99-ARIC-MN-Whites), and RPR=2.54 (1.74,3.72-ARIC-MS-AA). Understanding why risk factors differ by race and region likely requires diverse samples and harmonized methods using culturally-appropriate assessments.

Abstract Plasma-based biomarkers of amyloid beta (Aβ), a neuropathological hallmark of Alzheimer’s disease, show promise in predicting cognitive impairment and mapping onto cerebral amyloidosis, but little is known about how midlife plasma Aβ associates with late-life cognitive outcomes. Midlife plasma variants Aβ42 and Aβ40 were measured using a fluorimetric bead-based immunoassay in a subsample of visit 3 ARIC participants (1993-95; n=2585, mean age=59.4±5.2, 57% female, 23% African American). We investigated the relationship between midlife plasma Aβ and late-life mild cognitive impairment (MCI; n=923) and dementia (n=628) diagnosed from 2011-19. Multinomial logistic regressions estimated relative risk ratios (RRR) of MCI, dementia, and death vs normal cognitive status as a function of:(1) Aβ42:Aβ40 ratio, (2) Aβ42 and Aβ40 included as separate terms, and (3) Protected Aβ group (participants with Aβ42≥46 pg/ml and Aβ40 <233 pg/ml). Adjusters included age, sex, education, site-race, and APOE4. Every doubling of midlife plasma Aβ42:Aβ40 up to a threshold of 0.20 was associated with 41% lower risk of developing MCI/dementia in comparison to cognitively normal (RRR=0.59 [95% CI:0.42, 0.82]), with no association for ratio values ≥0.20. Every standard deviation increase in plasma Aβ42 was associated with 17% lower risk of dementia (RRR=0.83 [0.70, 0.99]), whereas every standard deviation increase in plasma Aβ40 was associated with 16% higher risk of MCI (RRR=1.16 [1.02, 1.31]). The protected midlife plasma Aβ group had 86% lower risk of late-life dementia vs all others (RRR=0.14 [0.04, 0.47]). Early measurement of plasma Aβ may prove an accessible and effective population screener for future cognitive impairment.

Background: Vascular aging is associated with cognitive decline. Aortic stiffness is a hallmark of vascular aging. We tested the hypothesis that greater aortic stiffness is associated with a faster rate of cognitive decline over 5 years among older adults. Methods: A prospective cohort study at the 5th (2011-2013) and 6th (2016-2017) examinations of the Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS) was conducted to quantify the association between baseline aortic stiffness and cognitive decline over 5 years. A total of 4639 participants (mean age: 75 years, 41% men, 22% Black) with baseline measures of aortic stiffness and cognitive function were included in the analysis. Aortic stiffness was measured as carotid-femoral pulse wave velocity (cfPWV) using the Omron VP-1000 Plus device and analyzed continuously per 1 standard deviation meter/second (3.20 m/s). Elevated aortic stiffness was defined as the upper 25th percentile of cfPWV (13.39 m/s). Cognitive function was based on ten neuropsychological tests across multiple domains of cognition, including memory, executive function/processing speed, and language. A global cognitive performance factor score was estimated based on all cognitive tests at both visits. Multivariable linear regression was used to examine the associations of each standard deviation (SD) increment in cfPWV and elevated cfPWV with annual cognitive decline over 5 years. Interactions with baseline cognitive status were assessed. To account for attrition (35% over 5 years), multiple imputation by chained equations was used to impute missing global cognitive performance factor scores at visit 6. Results: Each 1 SD increase in cfPWV was associated with 0.008 SD (Beta (β)=-0.008, 95% confidence interval (CI): -0.010, -0.003) annual rate of decline in cognitive function after adjustment for age, sex, education, race-center and ApoE4. With additional adjustment for ever smoking, total weekly physical activity time, mean arterial pressure, diabetes, and body mass index, each SD higher cfPWV was associated with 0.005 SD (β=-0.005, 95% CI: -0.010, -0.001) annual rate of decline in cognitive function. Elevated cfPWV was associated with 0.015 SD (β=-0.015, 95% CI: -0.024, -0.005) annual decline in cognitive function, and with 0.010 SD (β=-0.010, 95% CI: -0.020, 0.0001) annual decline after additional adjustment. Conclusion: Higher aortic stiffness is associated with the rate of decline in global cognitive function among community-dwelling older adults. The hemodynamic sequelae of aortic stiffening may contribute to cognitive decline among older adults.

Background Atrial fibrillation (AF) is a risk factor for cognitive decline, possibly from silent brain infarction. Left atrial changes in structure or function (atrial cardiopathy) can lead to AF but may impact cognition independently. It is unknown if AF or atrial cardiopathy also acts on Alzheimer disease–specific mechanisms, such as deposition of β‐amyloid. Methods and Results A total of 316 dementia‐free participants from the ARIC (Atherosclerosis Risk in Communities) study underwent florbetapir positron emission tomography, electrocardiography, and 2‐dimensional echocardiography. Atrial cardiopathy was defined as ≥1: (1) left atrial volume index >34 mL/m 2 ; (2) P‐wave terminal force >5000 µV×ms; and (3) serum NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) >250 pg/mL. Cross‐sectional associations between global cortical β‐amyloid (>1.2 standardized uptake value ratio) and adjudicated history of AF and atrial cardiopathy, each, were evaluated using multivariable logistic regression. Participants (mean age, 76 years) were 56% women and 42% Black individuals. Odds of elevated florbetapir standardized uptake value ratio were significantly increased among those with atrial cardiopathy (odds ratio, 1.81; 95% CI, 1.02–3.22) and doubled for those with enlarged left atrial volume index after adjustment for demographics/risk factors (95% CI, 1.04–4.61). There was no association between P‐wave terminal force or NT‐proBNP and elevated florbetapir standardized uptake value ratio, nor between AF and elevated standardized uptake value ratio. Conclusions Among healthy, nondemented community‐dwelling older individuals, we report an association between atrial cardiopathy, left atrial volume index, and elevated brain amyloid, by positron emission tomography, without a similar association in individuals with AF. Potential limitations include reverse causation and survival bias. Ongoing work will help determine if changes in cardiac structure and function precede or occur simultaneously with amyloid deposition.

AbstractBackgroundWhite matter (WM) changes are widely seen in the elderly due to aging and pathological processes and have significant impact on cognitive aging. It is critical to understand the heterogeneity and drivers (causes) of the longitudinal deterioration of WM microstructural integrity, especially in a population‐based sample, to provide mechanistic insights into cognitive and brain aging.MethodLeveraging longitudinal diffusion tensor imaging (DTI) data from Mayo Clinic Study of Aging, we assessed whether individuals clustered based on distinct longitudinal fractional anisotropy (FA) trajectories. A total of 533 subjects (487 cognitively unimpaired, 62 with mild cognitive impairment and 4 with dementia diagnosis) aged ≥ 60 years and with at least two DTI scans (125 subjects had at least 3 scans) were included. To identify clusters of individuals with common FA profiles over time, we applied an in‐house longitudinal Bayesian mixed‐effects clustering analysis framework to the imaging data. Age at MRI accounted for the longitudinal component of the model, while sex and APOE4 carrier status were used as fixed effects.ResultWe identified four distinct clusters (Figure 1). We found that most WM tracts decline with age across all clusters but brainstem and association fibers were least likely to decline with aging. APOE4 carriership and amyloid deposition did not differ between the clusters. We found a resilient cluster of individuals (34%) (cluster 1) with better baseline WM and systemic vascular health who had a slower rate of cognitive and WM integrity decline over time. These individuals had highest baseline commissural and association fibers. The resilient group was in contrast to an “at risk” cluster of individuals (16%) (cluster 2) who had lower baseline WM integrity and systemic health and declined the fastest in both WM health and cognition over timeConclusionLongitudinal clustering of WM tracts provided insights into the differential aging of WM in the population which may be unrelated to Alzheimer’s disease pathophysiology. Measuring overall WM health and vulnerable tracts in the elderly can be useful as biomarkers and aid in the identification of “at risk” groups for prevention of future cognitive decline.

AbstractBackgroundDisproportionately enlarged subarachnoid‐space hydrocephalus (DESH), characterized by tight high convexity CSF spaces, ventriculomegaly, and enlarged Sylvian fissures, is thought to be an indirect marker of a CSF dynamics disorder. Although this imaging phenotype was originally described in normal pressure hydrocephalus (NPH), it has since been more widely recognized in the aging population with a prevalence of 6‐7% in the Mayo Clinic Study of Aging (MCSA) 1. The clinical significance of DESH with regards to cognitive decline outside of NPH is not yet well‐defined. The goal of this work is to determine if DESH is associated with risk of cognitive impairment.MethodParticipants in the population‐based MCSA who met the following criteria were included: age ≥ 65 years, 3T MRI, cognitively unimpaired at enrollment, and at least one follow‐up visit. A support vector machine based method to detect the DESH imaging features on T1‐weighted MRI was used to calculate “computational DESH” or CDESH scores2 (Figure 1). Cox proportional hazard models were fit with events defined as progression from cognitively unimpaired to mild cognitive impairment or dementia. Time was defined as years from MCSA enrollment to the first visit with cognitive impairment with censoring at last follow‐up. CDESH was modelled as a spline to allow for non‐linear effects. Covariates included age, sex, education, APOE status, cortical thickness, white matter hyperintensity (WMH) volume, and total intracranial volume.ResultParticipant demographics are summarized in Table 1. The model including the above co‐variates showed a significant CDESH effect (p=0.02) with an approximately 20% greater hazard of progression for a CDESH score of +1 versus −1 (HR 1.2, 95% CI 1.0‐1.4) (Figure 2).ConclusionImaging features of disordered CSF dynamics are an independent predictor of subsequent cognitive decline in the MCSA, among other well‐known factors including age, cortical thickness, and APOE status. Therefore, since DESH contributes to cognitive decline and is present in the general population, identifying individuals with DESH features may be important clinically and also used as a selection stratification variable for clinical trials. References: (1) Graff‐Radford et al doi:10.1212/WNL.0000000000008616; (2) N. Gunter et al doi:10.1016/j.nicl.2018.11.015.