Vemuri, Prashanthi

AbstractBackgroundStudies of aging and dementia often acquire brain MRI and PET images, then de‐identify and share these widely with other researchers. It is known that research participants can potentially be re‐identified from brain MRI and CT using face recognition, but this has not been tested with PET imaging.MethodWe generated face reconstruction images of 182 volunteers using their existing amyloid (PiB), tau (FTP), and FDG PET scans from clinical GE PET/CT scanners, and we measured how often commercial automatic face recognition (Microsoft Azure) correctly matched these reconstructions with photographs of their faces. We additionally compared these match rates with face reconstructions from CT (from PET/CT) and MRI. When testing face recognition from PET scans, CT was used only during PET reconstruction, not for face recognition. We also validated our updated mri_reface software, originally developed to de‐identify (“de‐face”) faces in MRI, with new support for PET images. We measured face recognition rates before and after applying mri_reface to PET, CT, and MRI. In addition, we measured effects of de‐facing on biomarker measurements (global and regional SUVR) using 244 ADNI Florbetapir (FBP) amyloid PET scans with two automated pipelines: FreeSurfer 6.0 (PETSurfer) and an in‐house SPM12‐based pipeline.ResultRates of successful face recognition with PET ranged from 32‐41% (Table 1) across tracers. These were lower than MRI (98%) and CT (78%) but still concerning for participant privacy. Using mri_reface reduced face recognition to 0‐3.5% for PET, 5% for CT, and 8% for MRI. mri_reface had little effect on global amyloid SUVR measurements from ADNI PET images (Figure 1). ICC values between original and de‐faced images were 1.00 with biases and median absolute differences < 0.5%, across both pipelines. Effects on individual regions all had ICC values > 0.98 with biases and median absolute differences < 2%.ConclusionFace reconstructions from PET images have sufficient quality for potential re‐identification using publicly available face recognition technology. Research studies should consider using face de‐identification (de‐facing) software on PET images in addition to CT and structural MRI. Our free, automatic mri_reface software greatly reduced the potential for face recognition without substantially affecting SUVR measurements.

Background: Observational studies suggested that dementia risk in patients with rheumatoid arthritis (RA) is higher than in the general population. Objective: To examine the associations of RA with cognitive decline and dementia, and neuroimaging biomarkers of aging, Alzheimer’s disease, and vascular pathology in adult participants in the Mayo Clinic Study of Aging (MCSA). Methods: Participants with RA were matched 1:3 on age, sex, education, and baseline cognitive diagnosis to participants without RA. RA cases with MRI were also matched with non-cases with available MRI. All available imaging studies (i.e., amyloid and FDG PET, sMRI, and FLAIR) were included. The study included 104 participants with RA and 312 without RA (mean age (standard deviation, SD) 75.0 (10.4) years, 33% male and average follow-up (SD) 4.2 (3.8) years). Results: Groups were similar in cognitive decline and risk of incident dementia. Among participants with neuroimaging, participants with RA (n = 33) and without RA (n = 98) had similar amyloid burden and neurodegeneration measures, including regions sensitive to aging and dementia, but greater mean white matter hyperintensity volume relative to the total intracranial volume (mean (SD)% : 1.12 (0.57)% versus 0.76 (0.69)% of TIV, p = 0.01), and had higher mean (SD) number of cortical infarctions (0.24 (0.44) versus 0.05 (0.33), p = 0.02). Conclusion: Although cognitive decline and dementia risk were similar in participants with and without RA, participants with RA had more abnormal cerebrovascular pathology on neuroimaging. Future studies should examine the mechanisms underlying these changes and potential implications for prognostication and prevention of cognitive decline in RA.

Background: Brain accumulation of amyloid-β is a hallmark event in Alzheimer’s disease (AD) whose underlying mechanisms are incompletely understood. Case-control genome-wide association studies have implicated numerous genetic variants in risk of clinically diagnosed AD dementia. Objective: To test for associations between case-control AD risk variants and amyloid PET burden in older adults, and to assess whether a polygenic measure encompassing these factors would account for a large proportion of the unexplained variance in amyloid PET levels in the wider population. Methods: We analyzed data from the Mayo Clinic Study of Aging (MCSA) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Global cortical amyloid PET burden was the primary outcome. The 38 gene variants from Wightman et al. (2021) were analyzed as predictors, with PRSice-2 used to assess the collective phenotypic variance explained. Results: Known AD risk variants in APOE, PICALM, CR1, and CLU were associated with amyloid PET levels. In aggregate, the AD risk variants were strongly associated with amyloid PET levels in the MCSA ( p = 1.51×10 –50 ) and ADNI ( p = 3.21×10 –64 ). However, in both cohorts the non- APOE variants uniquely contributed only modestly (MCSA = 2.1%, ADNI = 4.4%) to explaining variation in amyloid PET levels. Conclusion: Additional case-control AD risk variants added only modestly to APOE in accounting for individual variation in amyloid PET burden, results which were consistent across independent cohorts with distinct recruitment strategies and subject characteristics. Our findings suggest that advancing precision medicine for dementia may require integration of strategies complementing case-control approaches, including biomarker-specific genetic associations, gene-by-environment interactions, and markers of disease progression and heterogeneity.

AbstractIntroductionWe investigated the association of the area deprivation index (ADI) with cognitive decline, mild cognitive impairment (MCI), and dementia in older adults (≥50 years old). ADI is a neighborhood socioeconomic disadvantage measure assessed at the census block group level.MethodsThe study included 4699 participants, initially without dementia, with available ADI values for 2015 and at least one study visit in 2008 through 2018. Using logistic regression and Cox proportional hazards models with age as the time scale, we assessed the odds for MCI and the risk for dementia, respectively.ResultsIn cognitively unimpaired (CU) adults at baseline, the risk for progression to dementia increased for every decile increase in the ADI state ranking (hazard ratio = 1.06, 95% confidence interval (1.01–1.11), P = .01). Higher ADI values were associated with subtly faster cognitive decline.DiscussionIn older CU adults, higher baseline neighborhood socioeconomic deprivation levels were associated with progression to dementia and slightly faster cognitive decline.Highlights The study used area deprivation index, a composite freely available neighborhood deprivation measure. Higher levels of neighborhood deprivation were associated with greater mild cognitive impairment odds. Higher neighborhood deprivation levels were associated with higher dementia risk.

Abstract Background This study aimed to examine if the association of cerebral perfusion with gait speed differs across systolic blood pressure (SBP) and age. Methods Cerebral perfusion was measured via arterial spin labeled (ASL)-MRI among community-dwelling adults aged 31–94 years in the population-based Mayo Clinic Study of Aging. Usual gait speed was assessed over 5.6 meters on an electronic mat. Sex- and body mass index (BMI)-adjusted linear regression models estimated cross-sectional gait speed associations with ASL and modifying effects of age and SBP using 3-way and 2-way interaction terms between continuous age, SBP, and ASL. Results report estimated differences in gait speed per standard deviation (SD) lower ASL for exemplar SBPs and ages. Results Among 479 participants (mean age 67.6 years; 44% women; mean gait speed 1.17 m/s), ASL relations to gait speed varied by age (ASL-x–age interaction: p = .001) and SBP (ASL-x–SBP interaction: p = .009). At an SBP of 120 mmHg, each SD lower ASL was associated with a 0.04 m/s (95% confidence interval [CI]: 0.01, 0.07) slower gait speed at 65 years, 0.07 m/s (0.04, 0.10) at 75 years, and 0.09 m/s (0.05, 0.13) at 85 years. At an SBP of 140 mmHg, ASL associations with gait speed were attenuated to 0.01 (−0.01, 0.04), 0.04 (0.02, 0.06), and 0.06 (0.04, 0.09) m/s slower gait speed at ages 65, 75, and 85, respectively. Conclusion Poorer cerebral perfusion is associated with clinically meaningful slower gait speeds, particularly with older age, while higher perfusion markedly attenuates age differences in gait speed.

Abstract Introduction We have previously shown that older adults with excessive daytime sleepiness (EDS) appear to be more vulnerable to longitudinal amyloid PET accumulation before the onset of the dementia. It remains unclear whether this vulnerability is specific to amyloid or extends to other biomarkers of Alzheimer’s disease pathology, or axonal integrity and inflammation, which can also contribute to neurodegeneration and cognitive changes. Methods For this cross-sectional analysis, we identified 260 cognitively unimpaired adults (&gt;60 years old) without neurologic disorder who underwent CSF quantification of AD biomarkers (CSF Aβ-42, p-tau181, p-tau217) along with at least one other biomarker of interest (neurofilament light chain [NfL], IL-6, IL-10, and TNF-α) from the Mayo Clinic Study of Aging – a longitudinal population-based cohort in Olmsted County, Minnesota. CSF biomarkers were available in 251-260 individuals, depending on the biomarker. We fit linear regression models to assess whether the CSF biomarkers were associated with sleepiness as measured by the Epworth Sleepiness Scale (ESS), after controlling for age, sex, APOE4 genotype, BMI, hypertension, dyslipidemia, and OSA diagnosis (by chart review). Results Higher ESS scores were independently associated with higher CSF IL-6 and NfL, but not with the other biomarkers in the whole sample. For every single-point increase in the ESS score, there was a .008 ([95% CI .001-.016], p=0.033) increase in the log of IL-6 and .01 ([95% CI .002-.018], p=0.016) increase in the log of NfL. A sensitivity analysis showed a correlation between ESS scores and log of p-tau/Aβ-42 ratio only in participants with abnormal ratio (&gt;0.023), after controlling for APOE4 (partial r=.27, p=039). Conclusion Our results corroborate previous literature suggesting that higher inflammatory milieu reflected by increased CSF IL-6 is associated with sleepiness. The association between NfL and sleepiness suggests that sleepiness may be related to disturbed connectivity due to axonal damage. Alternatively, NfL may be a surrogate of active axonal injury associated with more disrupted sleep. A correlation between sleepiness and CSF p-tau/ab-42 ratio was only seen in patients with abnormal ratio, suggesting a stronger association between sleepiness and AD pathology as the disease progresses, possibly because AD pathology worsens sleep quality and/or vice-versa. Support (If Any) NIH/NIA

Background: Cerebral microbleeds (CMBs) are a common vascular pathology associated with future intracerebral hemorrhage. Plasma biomarkers of amyloid, tau, and neurodegeneration may provide a screening avenue to identify those with CMBs, but evidence is conflicting. Objective: To determine the association between plasma biomarkers (Aβ40, Aβ42, t-tau, p-tau181, p-tau217, neurofilament light chain (NfL)) and CMBs in a population-based study of aging and whether these biomarkers predict higher signal on Aβ-PET imaging in patients with multiple CMBs. Methods: 712 participants from the Mayo Clinic Study of Aging with T2* GRE MRI and plasma biomarkers were included. Biomarkers were analyzed utilizing Simoa (Aβ40, Aβ42, t-tau, NfL) or Meso Scale Discovery (p-tau181, p-tau217) platforms. Cross-sectional associations between CMBs, plasma biomarkers and Aβ-PET were evaluated using hurdle models and multivariable regression models. Results: Among the 188 (26%) individuals with≥1 CMB, a lower plasma Aβ42/Aβ40 ratio was associated with more CMBs after adjusting for covariables (IRR 568.5 95% CI 2.8–116,127). No other biomarkers were associated with risk or number CMBs. In 81 individuals with≥2 CMBs, higher plasma t-tau, p-tau181, and p-tau217 all were associated with higher Aβ-PET signal, with plasma p-tau217 having the strongest predictive value (r2 0.603, AIC –53.0). Conclusion: Lower plasma Aβ42/Aβ40 ratio and higher plasma p-tau217 were associated with brain amyloidosis in individuals with CMBs from the general population. Our results suggest that in individuals with multiple CMBs and/or lobar intracranial hemorrhage that a lower plasma Aβ42/Aβ40 ratio or elevated p-tau217 may indicate underlying cerebral amyloid angiopathy.

Introduction: Cerebrovascular disease (CVD) and neuropsychiatric symptoms (NPS) are common in older adults and are independently associated with cognitive impairment. In addition, vascular depression (a late-life depression) is hypothesized to be associated with cerebrovascular pathology. Hypothesis: CVD pathology imaging biomarkers (e.g., white matter hyperintensities (WMH), infarctions) are associated with depression and anxiety, and both (depression/anxiety and CVD imaging biomarkers) are independently associated with mild cognitive impairment (MCI). Methods: This cross-sectional study included 1739 Mayo Clinic Study of Aging participants (≥50 years old) without dementia, with comprehensive cognitive evaluations and available data on the Beck Depression Inventory II (BDI), the Beck Anxiety Inventory (BAI) and imaging CVD biomarkers via FLAIR-MRI (i.e., WMH% of total intracranial volume (TIV) and brain infarctions). We used linear and logistic regression models to examine the associations adjusting for age, sex, education, and apolipoprotein E ε4 status. Results: Participants’ mean age (SD) was 71.11 (10.61) years (53.3% males). Higher WMH% TIV burden was significantly associated with higher BDI (b= 0.082, 95%CI: 0.031, 0.133), p=0.002) and BAI scores (b= 0.088, 95%CI: 0.037, 0.140), p=0.001); the presence of infarctions was also associated with a higher BDI score. Both WMH %TIV burden (OR: 1.20 (95%CI:1.05, 1.38), p=0.008) and BDI score (OR: 1.38 (95%CI:1.21, 1.57), p<0.001) were significantly associated with MCI when included simultaneously in the model. We observed similar associations for CVD biomarkers and BAI score with MCI. Conclusions: CVD imaging biomarkers and NPS, as measured by BDI and BAI scores, could represent two distinct processes associated with cognitive impairment. Studies are ongoing to further examine these associations and delineate how CVD, NPS, and other pathophysiology processes (e.g., Alzheimer’s disease) interact and are associated with cognitive impairment.

Abstract Preclinical Alzheimer’s disease describes some individuals who harbour Alzheimer’s pathologies but are asymptomatic. For this study, we hypothesized that genetic variation may help protect some individuals from Alzheimer’s-related neurodegeneration. We therefore conducted a genome-wide association study using 5 891 064 common variants to assess whether genetic variation modifies the association between baseline beta-amyloid, as measured by both cerebrospinal fluid and positron emission tomography, and neurodegeneration defined using MRI measures of hippocampal volume. We combined and jointly analysed genotype, biomarker and neuroimaging data from non-Hispanic white individuals who were enrolled in four longitudinal ageing studies (n = 1065). Using regression models, we examined the interaction between common genetic variants (Minor Allele Frequency &gt;0.01), including APOE-ɛ4 and APOE-ɛ2, and baseline cerebrospinal levels of amyloid (CSF Aβ42) on baseline hippocampal volume and the longitudinal rate of hippocampal atrophy. For targeted replication of top findings, we analysed an independent dataset (n = 808) where amyloid burden was assessed by Pittsburgh Compound B ([11C]-PiB) positron emission tomography. In this study, we found that APOE-ɛ4 modified the association between baseline CSF Aβ42 and hippocampal volume such that APOE-ɛ4 carriers showed more rapid atrophy, particularly in the presence of enhanced amyloidosis. We also identified a novel locus on chromosome 3 that interacted with baseline CSF Aβ42. Minor allele carriers of rs62263260, an expression quantitative trait locus for the SEMA5B gene (P = 1.46 × 10−8; 3:122675327) had more rapid neurodegeneration when amyloid burden was high and slower neurodegeneration when amyloid was low. The rs62263260 × amyloid interaction on longitudinal change in hippocampal volume was replicated in an independent dataset (P = 0.0112) where amyloid burden was assessed by positron emission tomography. In addition to supporting the established interaction between APOE and amyloid on neurodegeneration, our study identifies a novel locus that modifies the association between beta-amyloid and hippocampal atrophy. Annotation results may implicate SEMA5B, a gene involved in synaptic pruning and axonal guidance, as a high-quality candidate for functional confirmation and future mechanistic analysis.