Mielke, Michelle M.

AbstractBackgroundThe Mayo Clinic Study of Aging and Alzheimer’s Disease Research Center used GE scanners exclusively for MRI from 2005‐2017, employing consistent imaging parameters throughout. In 2017 the MRI protocol was updated and migrated to Siemens Prisma scanners; 113 participants were scanned with each configuration. The GE protocol included a 2D FLAIR. The Siemens protocol includes 3D FLAIR and T2‐weighted images. Both vendor protocols included a 3D T1. Experience with multi‐center trials suggests such changes may introduce systematic variations.MethodsGE scanning was carried out on 3T scanners with 12 channel phased array head coils. Siemens Prisma scanning was carried out with 64 channel head/neck coils. Imaging sequences and parameters are given in Table 1. We used the MCALT template and priors to perform standard six‐class segmentation on T1‐weighted (T1w) images. SPM12 unified segmentation supports the simultaneous use of multiple input contrasts; segmentation of multi‐contrast inputs was done using eight tissue classes including deep grey and white matter hyperintensity (WMH) priors. For a given MRI study (either GE or Siemens) all images were registered and resampled to the study’s T1w image. Two‐channel (T1+FLAIR) segmentation was performed on GE scans. Two and three‐channel segmentations were performed on Siemens scans. Comparisons included total intracranial volume, total tissue volume and total grey matter volumes, as well as hippocampal volumes and grey matter volume in a temporal lobe meta‐ROI.ResultsFour participants were excluded for poor image quality: one poor GE T1w quality, one poor Siemens T1, T2 and FLAIR quality, and two poor Siemens T2 quality. Comparisons were made among 109 participants aged 34–97 (Table 2). By visual assessment, adding T2‐weighted images always improved intracranial volume correctness. Using the combination of single‐channel GE and three‐channel Siemens generally improved cross‐vendor agreement on grey matter volumes with the exceptions of hippocampal and intracranial volume estimates.ConclusionRequiring multiple input channels increases the likelihood that the result of a study being excluded. Combining T1w, FLAIR and T2w images allows the delineation of WMH and deep grey matter probability outputs but may introduce differences in GM volumes.

AbstractBackgroundEarly changes in white matter (WM) measured using diffusion tensor imaging (DTI) are sensitive markers of WM degeneration and predict future cognitive decline in mild cognitive impairment (MCI). We sought to examine whether changes in WM integrity differed among empirically derived subtypes of incident MCI.MethodParticipants included 66 individuals with incident MCI enrolled in the population‐based Mayo Clinic Study of Aging (MCSA) previously identified via cluster analysis as having one of four MCI subtypes: subtle cognitive impairment (SCI; n = 13, mean age 78; 15% women), amnestic (n = 24; mean age 79; 54% women), dysnomic (n = 8; mean age 79; 38% women), and dysexecutive (n = 21; mean age 82; 33% women). All participants completed 3T MRI at the time of the MCI diagnosis. We compared the MCI subtypes to 100 cognitively unimpaired (CU) participants (mean age 77; 49% women). We used tract‐based spatial statistics to examine voxel‐level differences in fractional anisotropy (FA). We also fit a linear regression model to regional FA data from the corpus callosum (CC), the major interhemispheric WM connection, to quantify the relative differences in WM damage.ResultAll MCI subtypes except the subtle cognitive impairment group had widespread decreased FA. Relative to CU, the amnestic cluster showed decreased FA in the CC (genu), cingulum, fornix and uncinate fasciculus (UF); the dysnomic cluster showed decreased FA in the CC (genu, splenium), fornix, UF, anterior thalamic radiation (ATR), and corticospinal tract (CST); and the dysexecutive group showed decreased FA in the CC (genu, body, splenium), cingulum, UF, ATR, CST, and superior longitudinal fasciculus. The dysexecutive cluster had the most severe bilateral involvement among all MCI subtypes. The regional analysis showed that the amnestic, dysnomic, and dysexecutive groups (but not the subtle cognitive impairment group) had significantly lower FA of the CC compared to CU (p<0.001; Figure 1).ConclusionWe found widespread WM degeneration in the commissural and long association fibers in amnestic, dysnomic, and dysexecutive incident MCI subtypes. The extent of CC damage seen in Figure 1. confirmed the voxel‐level results and suggests that interhemispheric WM disconnection is relevant to the development of MCI.

Abstract Study Objectives To analyze cognitive deficits leading to unsafe driving in patients with REM Sleep Behavior Disorder (RBD), strongly associated with cognitive impairment and synucleinopathy-related neurodegeneration. Methods Twenty isolated RBD (iRBD), 10 symptomatic RBD (sRBD), and 20 age- and education-matched controls participated in a prospective case-control driving simulation study. Group mean differences were compared with correlations between cognitive and driving safety measures. Results iRBD and sRBD patients were more cognitively impaired than controls in global neurocognitive functioning, processing speeds, visuospatial attention, and distractibility (p &lt; .05). sRBD patients drove slower with more collisions than iRBD patients and controls (p &lt; .05), required more warnings, and had greater difficulty following and matching speed of a lead car during simulated car-following tasks (p &lt; .05). Driving safety measures were similar between iRBD patients and controls. Slower psychomotor speed correlated with more off-road accidents (r = 0.65) while processing speed (−0.88), executive function (−0.90), and visuospatial impairment (0.74) correlated with safety warnings in sRBD patients. Slower stimulus recognition was associated with more signal-light (0.64) and stop-sign (0.56) infractions in iRBD patients. Conclusions iRBD and sRBD patients have greater selective cognitive impairments than controls, particularly visuospatial abilities and processing speed. sRBD patients exhibited unsafe driving behaviors, associated with processing speed, visuospatial awareness, and attentional impairments. Our results suggest that iRBD patients have similar driving-simulator performance as healthy controls but that driving capabilities regress as RBD progresses to symptomatic RBD with overt signs of cognitive, autonomic, and motor impairment. Longitudinal studies with serial driving simulator evaluations and objective on-road driving performance are needed.

Abstract Women with premenopausal bilateral oophorectomy (PBO) are at increased risk for physical function (PF) declines. This study investigated the relationships of field-based physical activity measures with clinical PF and strength parameters in post-menopausal women with and without PBO. Women with (n=21; age=64±4 years; BMI=32±8 kg.m-2) and without (n=15; age=67±6 years; BMI=28±6 kg.m-2) PBO performed PF and strength tests (walking speed, distance walked, short physical performance battery (SPBB), leg and chest strength), and wore ankle accelerometers for 7 days (daily step count and loading index [the cumulative sum of each step’s skeletal loading]). Age, BMI, step count and loading index were entered into stepwise multiple regression to identify significant predictors of PF and strength parameters. Step count was a predictor of SPBB score in both groups. In women without PBO, step count was a predictor of walking speed; loading index was a predictor of leg strength; step count and loading index were predictors of distance; and step count and age were predictors of chest strength. For PBO women, loading index and BMI were predictors of walking speed and distance; BMI was a predictor of leg strength; and there were no predictors of chest strength. These data suggest while field-based physical activity was strongly and positively associated with clinical PF and strength measures for women without PBO, BMI was a dominant negative factor for PF in women with PBO. Future work will include a larger sample size and additional confounders to further elucidate underlying factors of reduced PF and mobility after PBO.

AbstractIntroductionBlood‐based biomarkers of amyloid pathology and neurodegeneration are entering clinical use. It is critical to understand what factors affect the levels of these markers.MethodsPlasma markers (Aβ42, Aβ40, NfL, T‐tau, Aβ42/40 ratio) were measured on the Quanterix Simoa HD‐1 analyzer for 996 Mayo Clinic Study of Aging (MCSA) participants, aged 51 to 95 years. All other data were collected during in‐person MCSA visits or abstracted from the medical record.ResultsAmong cognitively unimpaired (CU) participants, all plasma markers correlated with age. Linear regression models revealed multiple relationships. For example, higher Charlson Comorbidity Index and chronic kidney disease were associated with higher levels of all biomarkers. Some relationships differed between mild cognitive impairment and dementia participants.DiscussionMultiple variables affect plasma biomarkers of amyloid pathology and neurodegeneration among CU in the general population. Incorporating this information is critical for accurate interpretation of the biomarker levels and for the development of reference ranges.

AbstractIntroductionEfforts to model the cost‐effectiveness of managing/modifying cognitive impairment lack reliable, objective, baseline medical, and nursing‐home (NH) costs.MethodsA stratified‐random sample of Olmsted County, MN, residents ages 70–89 years (N = 3545), well‐characterized as cognitively unimpaired, mild cognitive impairment (MCI), or dementia, were followed forward ≤1 year in provider‐linked billing data and the Centers for Medicare & Medicaid Services NH assessments. Direct medical/nursing home/medical + NH costs were estimated. Costs were stratified by vital status and NH‐use intensity (NH days/follow‐up days [0%, 1% to 24%, 25% to 99%, and 100%]). Between‐category mean‐annual cost differences were adjusted for patient characteristics and follow‐up days.ResultsCosts/follow‐up day distributions differed significantly across cognitive categories. Mean costs/follow‐up days were 2.5 to 18 times higher for decedents versus survivors. Among all persons with MCI, <9% with any NH use accounted for 18% of all total annual medical + NH costs. Adjusted‐between‐category comparisons revealed significantly higher medical and medical + NH costs for MCI versus cognitively unimpaired.DiscussionCost‐effectiveness for managing/modifying both MCI and dementia should consider end‐of‐life costs and NH‐use intensity. Results can help inform cost‐effectiveness models, predict future‐care needs, and aid decision‐making by individuals/providers/payers/policymakers.

Background: The modifying effect of sex on the relation between marital status and dementia has yet to be determined. Objective: To examine if sex modifies the association between marital status and incident dementia. Methods: Population-based samples from the Mayo Clinic Study of Aging (MCSA, N = 3,471) and the Gothenburg H70 Birth Cohort Study (H70-study, N = 913) were used. A multiplicative interaction term was used to analyze the modifying effect of sex on the relation between marital status (married versus not married) and incident dementia using Cox regression models. Further, risk of dementia by marital status was also evaluated in models separated by sex. Results: In the MCSA, there was an interaction between marital status and sex in relation to dementia (p = 0.015). In contrast, in the H70-study, no significant interaction was observed (p = 0.28). Nevertheless, in both studies, not married men had increased risk of dementia compared to married men in models adjusted for age, education, and number of children (H70-study: 1.99; 1.06–3.76, MCSA: 1.43; 1.08–1.89). Associations remained similar after additional adjustment for depression, BMI, hypertension, dyslipidemia, and diabetes mellitus (H70-study: 2.00; 1.05–3.82, MCSA: 1.32; 0.99–1.76). Further, no significant association was observed between marital status and dementia in women (H70-study: 1.24; 0.82–1.89, MCSA: 0.82; 0.64–1.04). Conclusion: Sex had a modifying effect on the association between marital status and incident dementia. In analyses separated by sex, not married men had an increased risk of dementia compared to married men, while no significant association was observed between marital status and risk of dementia in women.

Background: Longitudinal, but not cross-sectional, cognitive testing is one option proposed to define transitional cognitive decline for individuals on the Alzheimer’s disease continuum. Objective: Compare diagnostic accuracy of cross-sectional subtle objective cognitive impairment (sOBJ) and longitudinal objective decline (ΔOBJ) over 30 months for identifying 1) cognitively unimpaired participants with preclinical Alzheimer’s disease defined by elevated brain amyloid and tau (A+T+) and 2) incident mild cognitive impairment (MCI) based on Cogstate One Card Learning (OCL) accuracy performance. Methods: Mayo Clinic Study of Aging cognitively unimpaired participants aged 50 + with amyloid and tau PET scans (n = 311) comprised the biomarker-defined sample. A case-control sample of participants aged 65 + remaining cognitively unimpaired for at least 30 months included 64 who subsequently developed MCI (incident MCI cases) and 184 controls, risk-set matched by age, sex, education, and visit number. sOBJ was assessed by OCL z-scores. ΔOBJ was assessed using within subjects’ standard deviation and annualized change from linear regression or linear mixed effects (LME) models. Concordance measures Area Under the ROC Curve (AUC) or C-statistic and odds ratios (OR) from conditional logistic regression models were derived. sOBJ and ΔOBJ were modeled jointly to compare methods. Results: sOBJ and ΔOBJ-LME methods differentiated A+T+ from A-T- (AUC = 0.64, 0.69) and controls from incident MCI (C-statistic = 0.59, 0.69) better than chance; other ΔOBJ methods did not. ΔOBJ-LME improved prediction of future MCI over baseline sOBJ (p = 0.003) but not over 30-month sOBJ (p = 0.09). Conclusion: Longitudinal decline did not offer substantial benefit over cross-sectional assessment in detecting preclinical Alzheimer’s disease or incident MCI.