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Abstract Background Obstructive sleep apnea (OSA) increases risk for cognitive decline and Alzheimer’s disease (AD). While the underlying mechanisms remain unclear, hypoxemia during OSA has been implicated in cognitive impairment. OSA during rapid eye movement (REM) sleep is usually more severe than in non-rapid eye movement (NREM) sleep, but the relative effect of oxyhemoglobin desaturation during REM versus NREM sleep on memory is not completely characterized. Here, we examined the impact of OSA, as well as the moderating effects of AD risk factors, on verbal memory in a sample of middle-aged and older adults with heightened AD risk. Methods Eighty-one adults (mean age:61.7 ± 6.0 years, 62% females, 32% apolipoprotein E ε4 allele (APOE4) carriers, and 70% with parental history of AD) underwent clinical polysomnography including assessment of OSA. OSA features were derived in total, NREM, and REM sleep. REM-NREM ratios of OSA features were also calculated. Verbal memory was assessed with the Rey Auditory Verbal Learning Test (RAVLT). Multiple regression models evaluated the relationships between OSA features and RAVLT scores while adjusting for sex, age, time between assessments, education years, body mass index (BMI), and APOE4 status or parental history of AD. The significant main effects of OSA features on RAVLT performance and the moderating effects of AD risk factors (i.e., sex, age, APOE4 status, and parental history of AD) were examined. Results Apnea–hypopnea index (AHI), respiratory disturbance index (RDI), and oxyhemoglobin desaturation index (ODI) during REM sleep were negatively associated with RAVLT total learning and long-delay recall. Further, greater REM-NREM ratios of AHI, RDI, and ODI (i.e., more events in REM than NREM) were related to worse total learning and recall. We found specifically that the negative association between REM ODI and total learning was driven by adults 60 + years old. In addition, the negative relationships between REM-NREM ODI ratio and total learning, and REM-NREM RDI ratio and long-delay recall were driven by APOE4 carriers. Conclusion Greater OSA severity, particularly during REM sleep, negatively affects verbal memory, especially for people with greater AD risk. These findings underscore the potential importance of proactive screening and treatment of REM OSA even if overall AHI appears low.

Abstract In this study, we aimed to understand the potential role of the gut microbiome in the development of Alzheimer's disease (AD). We took a multi-faceted approach to investigate this relationship. Urine metabolomics were examined in individuals with AD and controls, revealing decreased formate and fumarate concentrations in AD. Additionally, we utilised whole-genome sequencing (WGS) data obtained from a separate group of individuals with AD and controls. This information allowed us to create and investigate host-microbiome personalised whole-body metabolic models. We predicted microbial formate as well as other microbial metabolites, which could alter urine formate production in the host-microbiome personalised models. Additionally, we identified specific reactions responsible for the production of formate in the host, and interestingly, these reactions were linked to genes that have correlations with AD. This study suggests formate as a possible early AD marker and highlights genetic and microbiome contributions to its production. The reduced formate secretion and its genetic associations point to a complex connection between gut microbiota and AD. This holistic understanding might pave the way for novel diagnostic and therapeutic avenues in AD management.

Abstract Breakdown of the neurovascular unit is associated with blood-brain barrier (BBB) leakiness contributing to cognitive decline and disease pathology in the early stages of Alzheimer’s disease (AD). Vascular stability depends on angiopoietin-1 (ANGPT-1) signalling, antagonised by angiopoietin-2 (ANGPT-2) expressed upon endothelial injury. We examined the relationship between CSF ANGPT-2 and CSF markers of BBB leakiness and core AD biomarkers across three independent cohorts: (i) 31 AD patients and 33 healthy controls grouped according to their biomarker profile (i.e., AD cases t-tau > 400 pg/mL, p-tau > 60 pg/mL and Aβ42

Abstract Age-related disease may be mediated by low levels of chronic inflammation (“inflammaging”). Recent work suggests that gut microbes can contribute to inflammation via degradation of the intestinal barrier. While aging and age-related diseases including Alzheimer’s disease (AD) are linked to altered microbiome composition and higher levels of gut microbial components in systemic circulation, the role of intestinal inflammation remains unclear. To investigate whether greater gut inflammation is associated with advanced age and AD pathology, we assessed fecal samples from older adults to measure calprotectin, an established marker of intestinal inflammation which is elevated in diseases of gut barrier integrity. Multiple regression with maximum likelihood estimation and Satorra–Bentler corrections were used to test relationships between fecal calprotectin and clinical diagnosis, participant age, cerebrospinal fluid biomarkers of AD pathology, amyloid burden measured using 11C-Pittsburgh compound B positron emission tomography (PiB PET) imaging, and performance on cognitive tests measuring executive function and verbal learning and recall. Calprotectin levels were elevated in advanced age and were higher in participants diagnosed with amyloid-confirmed AD dementia. Additionally, among individuals with AD dementia, higher calprotectin was associated with greater amyloid burden as measured with PiB PET. Exploratory analyses indicated that calprotectin levels were also associated with cerebrospinal fluid markers of AD, and with lower verbal memory function even among cognitively unimpaired participants. Taken together, these findings suggest that intestinal inflammation is linked with brain pathology even in the earliest disease stages. Moreover, intestinal inflammation may exacerbate the progression toward AD.

Abstract Background Alzheimer’s disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical. Methods Participants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination). Results Using internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone. Conclusion Using a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged.

Abstract Background Insulin resistance (IR) and type 2 diabetes have been found to increase the risk for Alzheimer’s clinical syndrome in epidemiologic studies but have not been associated with tau tangles in neuropathological research and have been inconsistently associated with cerebrospinal fluid P-tau181. IR and type 2 diabetes are well-recognized vascular risk factors. Some studies suggest that cardiovascular risk may act synergistically with cortical amyloid to increase tau measured using tau PET. Utilizing data from largely nondemented middle-aged and older adult cohorts enriched for AD risk, we investigated the association of IR and diabetes to tau PET and whether amyloid moderated those relationships. Methods Participants were enrolled in either the Wisconsin Registry for Alzheimer’s Prevention (WRAP) or Wisconsin Alzheimer’s Disease Research Center (WI-ADRC) Clinical Core. Two partially overlapping samples were studied: a sample characterized using HOMA-IR (n=280 WRAP participants) and a sample characterized on diabetic status (n=285 WRAP and n=109 WI-ADRC). IR was measured using the homeostasis model assessment of insulin resistance (HOMA-IR). Tau PET employing the radioligand 18F-MK-6240 was used to detect AD-specific aggregated tau. Linear regression tested the relationship of IR and diabetic status to tau PET standardized uptake value ratio (SUVR) within the entorhinal cortex and whether relationships were moderated by amyloid assessed by amyloid PET distribution volume ratio (DVR) and amyloid PET positivity status. Results Neither HOMA-IR nor diabetic status was significantly associated with tau PET SUVR. The relationship between IR and tau PET SUVR was not moderated by amyloid PET DVR or positivity status. The association between diabetic status and tau PET SUVR was not significantly moderated by amyloid PET DVR but was significantly moderated by amyloid PET positivity status. Among the amyloid PET-positive participants, the estimated marginal tau PET SUVR mean was higher in the diabetic (n=6) relative to the nondiabetic group (n=88). Conclusion Findings indicate that IR may not be related to tau in generally healthy middle-aged and older adults who are in the early stages of the AD clinicopathologic continuum but suggest the need for additional research to investigate whether a synergistic relationship between type 2 diabetes and amyloid is associated with increased tau levels.

IntroductionMetabolomics technology facilitates studying associations between small molecules and disease processes. Correlating metabolites in cerebrospinal fluid (CSF) with Alzheimer’s disease (AD) CSF biomarkers may elucidate additional changes that are associated with early AD pathology and enhance our knowledge of the disease.MethodsThe relative abundance of untargeted metabolites was assessed in 161 individuals from the Wisconsin Registry for Alzheimer’s Prevention. A metabolome-wide association study (MWAS) was conducted between 269 CSF metabolites and protein biomarkers reflecting brain amyloidosis, tau pathology, neuronal and synaptic degeneration, and astrocyte or microglial activation and neuroinflammation. Linear mixed-effects regression analyses were performed with random intercepts for sample relatedness and repeated measurements and fixed effects for age, sex, and years of education. The metabolome-wide significance was determined by a false discovery rate threshold of 0.05. The significant metabolites were replicated in 154 independent individuals from then Wisconsin Alzheimer’s Disease Research Center. Mendelian randomization was performed using genome-wide significant single nucleotide polymorphisms from a CSF metabolites genome-wide association study.ResultsMetabolome-wide association study results showed several significantly associated metabolites for all the biomarkers except Aβ42/40 and IL-6. Genetic variants associated with metabolites and Mendelian randomization analysis provided evidence for a causal association of metabolites for soluble triggering receptor expressed on myeloid cells 2 (sTREM2), amyloid β (Aβ40), α-synuclein, total tau, phosphorylated tau, and neurogranin, for example, palmitoyl sphingomyelin (d18:1/16:0) for sTREM2, and erythritol for Aβ40 and α-synuclein.DiscussionThis study provides evidence that CSF metabolites are associated with AD-related pathology, and many of these associations may be causal.

Abstract Introduction It is critical to develop more inclusive Alzheimer's disease (AD) research protocols to ensure that historically excluded groups are included in preclinical research and have access to timely diagnosis and treatment. If validated in racialized groups, plasma AD biomarkers and measures of subtle cognitive dysfunction could provide avenues to expand diversity in preclinical AD research. We sought to evaluate the utility of two easily obtained, low‐burden disease markers, plasma amyloid beta (Aβ)42/40, and intra‐individual cognitive variability (IICV), to predict concurrent and longitudinal cognitive performance in a sample of Black adults. Methods Two hundred fifty‐seven Black participants enrolled in the African Americans Fighting Alzheimer's in Midlife (AA‐FAIM) study underwent at least one cognitive assessment visit; a subset of n = 235 had plasma samples. Baseline IICV was calculated as the standard deviation across participants’ z scores on five cognitive measures: Rey Auditory Verbal Learning Test Delayed Recall, Trail Making Test Parts A and B (Trails A and B), and Boston Naming Test. Using mixed effects regression models, we compared concurrent and longitudinal models to baseline plasma Aβ42/40 or IICV by age interactions. PrecivityAD assays quantified baseline plasma Aβ42/40. Results IICV was associated with concurrent/baseline performance on several outcomes but did not modify associations between age and cognitive decline. In contrast, plasma Aβ42/40 was unrelated to baseline cognitive performance, but a pattern emerged in interactions with age in longitudinal models of Trails A and B and Rey Auditory Verbal Learning Test total learning trials. Although not significant after correcting for multiple comparisons, low Aβ42/40 was associated with faster cognitive declines over time. Discussion Our results are promising as they extend existing findings to an Black American sample using low‐cost, low‐burden methods that can be implemented outside of a research center, thus supporting efforts for inclusive AD biomarker research.

Abstract Background The brain is the most cholesterol‐rich organ and myelin contains 70% of total brain cholesterol. Statins are potent cholesterol‐lowing medications used by millions of adults for prevention of vascular disease, yet the effect of statins on cholesterol‐rich brain white matter (WM) is largely unknown. Methods We used longitudinal neuroimaging data acquired from 73 healthy, cognitively unimpaired, statin‐naïve, middle‐aged adults during an 18‐month randomized controlled trial of simvastatin 40 mg daily (n = 35) or matching placebo (n = 38). ANCOVA models (covariates: age, sex, APOE‐ɛ4) tested the effect of treatment group on percent change in WM, gray matter (GM), and WM hyperintensity (WMH) neuroimaging measures at each study visit. Mediation analysis tested the indirect effects of simvastatin on WM microstructure through change in serum total cholesterol levels. Results At 18 months, the simvastatin group showed a significant preservation in global WM fractional anisotropy (β = 0.88%, 95% CI 0.27 to 1.50, P = 0.005), radial diffusivity (β = −1.10%, 95% CI −2.13 to −0.06, P = 0.039), and WM volume (β = 0.72%, 95% CI 0.13 to 1.32, P = 0.018) relative to the placebo group. There was no significant effect of simvastatin on GM or WMH volume. Change in serum total cholesterol mediated approximately 30% of the effect of simvastatin on WM microstructure. Conclusions Simvastatin treatment in healthy, middle‐aged adults resulted in preserved WM microstructure and volume at 18 months. The partial mediation by serum cholesterol reduction suggests both peripheral and central mechanisms. Future studies are needed to determine whether these effects persist and translate to cognitive outcomes. Trial Registration NCT00939822 (ClinicalTrials.gov).

Psychological well-being is associated with cognition in later life but has not been examined across diverse populations—including minoritized communities at disproportionately high risk of dementia. Further, most previous work has not been able to examine links between specific facets of psychological well-being and performance within distinct cognitive domains that can capture subclinical impairment. Using a well-characterized sample followed through enrollment in an NIH-funded Alzheimer’s Disease Center, we sought to test these associations within three racial groups at baseline. Participants were N = 529 cognitively unimpaired Black, American Indian/Alaska Native (AI/AN), and white middle-aged and older adults (mean age = 63.6, SD = 8.1, range = 45–88 years) enrolled in the Wisconsin Alzheimer’s Disease Research Center’s Clinical Core. Predictors included validated NIH Toolbox Emotion Battery scales assessing positive affect, general life satisfaction, and meaning and purpose. Outcomes included performance on widely used tests of executive functioning and episodic memory. We conducted race-stratified regression models to assess within-group relationships. Black and AI/AN participants reported lower life satisfaction than white participants. Racial disparities were not observed for positive affect or meaning and purpose scores. Across groups, life satisfaction predicted better executive functioning. Similar associations were observed for positive affect in Black and AI/AN samples but not among whites. In general, well-being measures were not related to performance on tests of episodic memory. Our results highlight well-being as a potentially important determinant of late-life cognitive health, particularly executive functioning, that is modifiable if older adults are connected with appropriate resources and supports. Further, psychological well-being may represent a potent target for brain health interventions tailored for Black and Native communities.

Here, the authors introduce a metabolome-wide association study that combines a genome-wide association study of cerebrospinal fluid metabolites with publicly available genome-wide association study summary statistics of neurological and psychiatric conditions to identify 19 significant CSF metabolite-phenotype associations.

BackgroundThe relationship between healthy and positive aging and dementia and cognitive impairment has received limited attention in the field of aging. Affect impacts cognitive changes and processes, and cognitive impairment is associated with affective comorbidities. The purpose of the study was to examine (a) whether happiness, helplessness, and hopelessness are linked to cognitive health status, and (b) whether these associations differ by race.MethodsParticipants were enrollees in the Wisconsin Alzheimer’s Disease Research Center’s Clinical Core (ADRC). Average age at baseline was 60.85 (SD = 8.65), 73.70 (SD = 8.02), and 73.80 (SD = 9.59) years for cognitively normal individuals, individuals with MCI, and individuals with dementia, respectively.ResultsIn the full sample, chi-square test results revealed associations between Cognitive Health Status (CHS) and (a) happiness, χ2(2) = 6.06, p < 0.05, (b) helplessness, χ2(2) = 6.44, p < 0.05, and (c) hopelessness, χ2(2) = 14.11, p < 0.01.ConclusionThis study provides support for the association of both positive and negative affect with cognitive health status in middle- to older-aged adults.

PurposeTo assess the pathological aging effect on caudate functional connectivity among mild cognitive impairment (MCI) participants and examine whether and how sex and amyloid contribute to this process.Materials and MethodsTwo hundred and seventy-seven functional magnetic resonance imaging (fMRI) sessions from 163 cognitive normal (CN) older adults and 309 sessions from 139 participants with MCI were included as the main sample in our analysis. Pearson's correlation was used to characterize the functional connectivity (FC) between caudate nuclei and each brain region, then caudate nodal strength was computed to quantify the overall caudate FC strength. Association analysis between caudate nodal strength and age was carried out in MCI and CN separately using linear mixed effect (LME) model with covariates (education, handedness, sex, Apolipoprotein E4, and intra-subject effect). Analysis of covariance was conducted to investigate sex, amyloid status, and their interaction effects on aging with the fMRI data subset having amyloid status available. LME model was applied to women and men separately within MCI group to evaluate aging effects on caudate nodal strength and each region's connectivity with caudate nuclei. We then evaluated the roles of sex and amyloid status in the associations of neuropsychological scores with age or caudate nodal strength. An independent cohort was used to validate the sex-dependent aging effects in MCI.ResultsThe MCI group had significantly stronger age-related increase of caudate nodal strength compared to the CN group. Analyzing women and men separately revealed that the aging effect on caudate nodal strength among MCI participants was significant only for women (left: P = 6.23 × 10−7, right: P = 3.37 × 10−8), but not for men (P > 0.3 for bilateral caudate nuclei). The aging effects on caudate nodal strength were not significantly mediated by brain amyloid burden. Caudate connectivity with ventral prefrontal cortex substantially contributed to the aging effect on caudate nodal strength in women with MCI. Higher caudate nodal strength is significantly related to worse cognitive performance in women but not in men with MCI.ConclusionSex modulates the pathological aging effects on caudate nodal strength in MCI regardless of amyloid status. Caudate nodal strength may be a sensitive biomarker of pathological aging in women with MCI.

Neurite orientation dispersion and density imaging (NODDI) is an advanced diffusion imaging technique, which can detect more distinct microstructural features compared to conventional Diffusion Tensor Imaging (DTI). NODDI allows the signal to be divided into multiple water compartments and derive measures for orientation dispersion index (ODI), neurite density index (NDI) and volume fraction of isotropic diffusion compartment (FISO). This study aimed to investigate which diffusion metric—fractional anisotropy (FA), mean diffusivity (MD), NDI, ODI, or FISO—is most influenced by aging and reflects cognitive function in a population of healthy older adults at risk for Alzheimer’s disease (AD). Age was significantly associated with all but one diffusion parameters and regions of interest. NDI and MD in the cingulate region adjacent to the cingulate cortex showed a significant association with a composite measure of Executive Function and was proven to partially mediate the relationship between aging and Executive Function decline. These results suggest that both DTI and NODDI parameters are sensitive to age-related differences in white matter regions vulnerable to aging, particularly among older adults at risk for AD.

Abstract Introduction Longitudinal cohort studies of cognitive aging must confront several sources of within‐person variability in scores. In this article, we compare several neuropsychological measures in terms of longitudinal error variance and relationships with biomarker‐assessed brain amyloidosis (Aβ). Methods Analyses used data from the Wisconsin Registry for Alzheimer's Prevention. We quantified within‐person longitudinal variability and age‐related trajectories for several global and domain‐specific composites and their constituent scores. For a subset with cerebrospinal fluid or amyloid positron emission tomography measures, we examined how Aβ modified cognitive trajectories. Results Global and theoretically derived composites exhibited lower intraindividual variability and stronger age × Aβ interactions than did empirically derived composites or raw scores from single tests. For example, the theoretical executive function outperformed other executive function scores on both metrics. Discussion These results reinforce the need for careful selection of cognitive outcomes in study design, and support the emerging consensus favoring composites over single‐test measures.

Abstract Introduction We investigated whether insulin resistance (IR) was associated with longitudinal age‐related change in cognition and biomarkers of Alzheimer's disease (AD) pathology and neurodegeneration in middle‐aged and older adults who were non‐demented at baseline. Methods IR was measured with homeostatic model assessment of insulin resistance (HOMA2‐IR). Core AD‐related cerebrospinal fluid (CSF) biomarkers and cognition were assessed, respectively, on n = 212 (1 to 5 visits) and n = 1299 (1 to 6 visits). Linear mixed models tested whether HOMA2‐IR moderated age‐related change in CSF biomarkers and cognition. Linear regressions tested whether HOMA2‐IR x apolipoprotein E ε4 allele (APOE ε4) carrier status predicted amyloid beta [Aβ] chronicity (estimated duration of amyloid positron emission tomography [PET] positivity) (n = 253). Results Higher HOMA2‐IR was associated with greater cognitive decline but not with changes in CSF biomarkers. HOMA2‐IR x APOE4 was not related to Aβ chronicity but was significantly associated with CSF phosphorylated tau (P‐tau)181/Aβ42 level. Discussion In non‐demented adults IR may not be directly associated with age‐related change in AD biomarkers. Additional research is needed to determine mechanisms linking IR to cognitive decline.

Abstract Introduction Cerebrospinal fluid (CSF) total tau (t‐tau) and phosphorylated tau (p‐tau) are biomarkers of Alzheimer's disease (AD), yet much is unknown about AD‐associated changes in tau metabolism and tau tangle etiology. Methods We assessed the variation of t‐tau and p‐tau explained by 38 previously identified CSF metabolites using linear regression models in middle‐age controls from the Wisconsin Alzheimer's Disease Research Center, and predicted AD/mild cognitive impairment (MCI) versus an independent set of older controls using metabolites selected by the least absolute shrinkage and selection operator (LASSO). Results The 38 CSF metabolites explained 70.3% and 75.7% of the variance in t‐tau and p‐tau, respectively. Of these, seven LASSO‐selected metabolites improved the prediction ability of AD/MCI versus older controls (area under the curve score increased from 0.92 to 0.97 and 0.78 to 0.93) compared to the base model. Discussion These tau‐correlated CSF metabolites increase AD/MCI prediction accuracy and may provide insight into tau tangle etiology.

Abstract Introduction Batch differences in cerebrospinal fluid (CSF) biomarker measurement can introduce bias into analyses for Alzheimer's disease studies. We evaluated and adjusted for batch differences using statistical methods. Methods A total of 792 CSF samples from 528 participants were assayed in three batches for 12 biomarkers and 3 biomarker ratios. Batch differences were assessed using Bland‐Altman plot, paired t test, Pitman‐Morgan test, and linear regression. Generalized linear models were applied to convert CSF values between batches. Results We found statistically significant batch differences for all biomarkers and ratios, except that neurofilament light was comparable between batches 1 and 2. The conversion models generally had high R2 except for converting P‐tau between batches 1 and 3. Discussion Between‐batch conversion allows harmonized CSF values to be used in the same analysis. Such method may be applied to adjust for other sources of variability in measuring CSF or other types of biomarkers.

Abstract Introduction Residence in a disadvantaged neighborhood associates with adverse health exposures and outcomes, and may increase risk for cognitive impairment and dementia. Utilization of a publicly available, geocoded disadvantage metric could facilitate efficient integration of social determinants of health into models of cognitive aging. Methods Using the validated Area Deprivation Index and two cognitive aging cohorts, we quantified Census block‐level poverty, education, housing, and employment characteristics for the neighborhoods of 2119 older adults. We assessed relationships between neighborhood disadvantage and cognitive performance in domains sensitive to age‐related change. Results Participants in the most disadvantaged neighborhoods (n = 156) were younger, more often female, and less often college‐educated or white than those in less disadvantaged neighborhoods (n = 1963). Disadvantaged neighborhood residence associated with poorer performance on tests of executive function, verbal learning, and memory. Discussion This geospatial metric of neighborhood disadvantage may be valuable for exploring socially rooted risk mechanisms, and prioritizing high‐risk communities for research recruitment and intervention.

Abstract Introduction This study applies a novel algorithm to longitudinal amyloid positron emission tomography (PET) imaging to identify age‐heterogeneous amyloid trajectory groups, estimate the age and duration (chronicity) of amyloid positivity, and investigate chronicity in relation to cognitive decline and tau burden. Methods Cognitively unimpaired participants (n = 257) underwent one to four amyloid PET scans (Pittsburgh Compound B, PiB). Group‐based trajectory modeling was applied to participants with longitudinal scans (n = 171) to identify and model amyloid trajectory groups, which were combined with Bayes theorem to estimate age and chronicity of amyloid positivity. Relationships between chronicity, cognition, clinical progression, and tau PET (MK‐6240) were investigated using regression models. Results Chronicity explained more heterogeneity in amyloid burden than age and binary amyloid status. Chronicity was associated with faster cognitive decline, increased risk of abnormal cognition, and higher entorhinal tau. Discussion Amyloid chronicity provides unique information about cognitive decline and neurofibrillary tangle development and may be useful to investigate preclinical Alzheimer's disease.

Abstract Background Trimethylamine N-oxide (TMAO), a small molecule produced by the metaorganismal metabolism of dietary choline, has been implicated in human disease pathogenesis, including known risk factors for Alzheimer’s disease (AD), such as metabolic, cardiovascular, and cerebrovascular disease. Methods In this study, we tested whether TMAO is linked to AD by examining TMAO levels in cerebrospinal fluid (CSF) collected from a large sample (n = 410) of individuals with Alzheimer’s clinical syndrome (n = 40), individuals with mild cognitive impairment (MCI) (n = 35), and cognitively-unimpaired individuals (n = 335). Linear regression analyses were used to determine differences in CSF TMAO between groups (controlling for age, sex, and APOE ε4 genotype), as well as to determine relationships between CSF TMAO and CSF biomarkers of AD (phosphorylated tau and beta-amyloid) and neuronal degeneration (total tau, neurogranin, and neurofilament light chain protein). Results CSF TMAO is higher in individuals with MCI and AD dementia compared to cognitively-unimpaired individuals, and elevated CSF TMAO is associated with biomarkers of AD pathology (phosphorylated tau and phosphorylated tau/Aβ42) and neuronal degeneration (total tau and neurofilament light chain protein). Conclusions These findings provide additional insight into gut microbial involvement in AD and add to the growing understanding of the gut–brain axis.

Abstract Background Age is the cardinal risk factor for Alzheimer’s disease (AD), and white matter hyperintensities (WMH), which are more prevalent with increasing age, may contribute to AD. Higher cardiorespiratory fitness (CRF) has been shown to be associated with cognitive health and decreased burden of AD-related brain alterations in older adults. Accordingly, the aim of this study was to determine whether CRF attenuates age-related accumulation of WMH in middle-aged adults at risk for AD. Methods One hundred and seven cognitively unimpaired, late-middle-aged adults from the Wisconsin Registry for Alzheimer’s Prevention underwent 3 T magnetic resonance imaging and performed graded maximal treadmill exercise testing from which we calculated the oxygen uptake efficiency slope (OUES) as our measure of CRF. Total WMH were quantified using the Lesion Segmentation Tool and scaled to intracranial volume. Linear regression adjusted for APOE4 carriage, family history, body mass index, systolic blood pressure, and sex was used to examine relationships between age, WMH, and CRF. Results As expected, there was a significant association between age and WMH (p

Abstract Mass spectrometry-based metabolomics has undergone significant progresses in the past decade, with a variety of software packages being developed for data analysis. However, systematic comparison of different metabolomics software tools has rarely been conducted. In this study, several representative software packages were comparatively evaluated throughout the entire pipeline of metabolomics data analysis, including data processing, statistical analysis, feature selection, metabolite identification, pathway analysis, and classification model construction. LC-MS-based metabolomics was applied to preclinical Alzheimer’s disease (AD) using a small cohort of human cerebrospinal fluid (CSF) samples (N = 30). All three software packages, XCMS Online, SIEVE, and Compound Discoverer, provided consistent and reproducible data processing results. A hybrid method combining statistical test and support vector machine feature selection was employed to screen key metabolites, achieving a complementary selection of candidate biomarkers from three software packages. Machine learning classification using candidate biomarkers generated highly accurate and predictive models to classify patients into preclinical AD or control category. Overall, our study demonstrated a systematic evaluation of different MS-based metabolomics software packages for the entire data analysis pipeline which was applied to the candidate biomarker discovery of preclinical AD.

Abstract The Wisconsin Registry for Alzheimer's Prevention is a longitudinal observational cohort study enriched with persons with a parental history (PH) of probable Alzheimer's disease (AD) dementia. Since late 2001, Wisconsin Registry for Alzheimer's Prevention has enrolled 1561 people at a mean baseline age of 54 years. Participants return for a second visit 4 years after baseline, and subsequent visits occur every 2 years. Eighty‐one percent (1270) of participants remain active in the study at a current mean age of 64 and 9 years of follow‐up. Serially assessed cognition, self‐reported medical and lifestyle histories (e.g., diet, physical and cognitive activity, sleep, and mood), laboratory tests, genetics, and linked studies comprising molecular imaging, structural imaging, and cerebrospinal fluid data have yielded many important findings. In this cohort, PH of probable AD is associated with 46% apolipoprotein E (APOE) ε4 positivity, more than twice the rate of 22% among persons without PH. Subclinical or worse cognitive decline relative to internal normative data has been observed in 17.6% of the cohort. Twenty‐eight percent exhibit amyloid and/or tau positivity. Biomarker elevations, but not APOE or PH status, are associated with cognitive decline. Salutary health and lifestyle factors are associated with better cognition and brain structure and lower AD pathophysiologic burden. Of paramount importance is establishing the amyloid and tau AD endophenotypes to which cognitive outcomes can be linked. Such data will provide new knowledge on the early temporal course of AD pathophysiology and inform the design of secondary prevention clinical trials.

Abstract Introduction Alzheimer's disease (AD) is characterized by the presence of amyloid β (Aβ) plaques, neurofibrillary tangles, and neurodegeneration, evidence of which may be detected in vivo via cerebrospinal fluid (CSF) sampling. Physical activity (PA) has emerged as a possible modifier of these AD‐related pathological changes. Consequently, the aim of this study was to cross‐sectionally examine the relationship between objectively measured PA and CSF levels of Aβ42 and tau in asymptomatic late‐middle‐aged adults at risk for AD. Methods Eighty‐five cognitively healthy late‐middle‐aged adults (age = 64.31 years, 61.2% female) from the Wisconsin Registry for Alzheimer's Prevention participated in this study. They wore an accelerometer (ActiGraph GT3X+) for one week to record free‐living PA, yielding measures of sedentariness and various intensities of PA (i.e., light, moderate, and vigorous). They also underwent lumbar puncture to collect CSF, from which Aβ42, total tau, and phosphorylated tau were immunoassayed. Regression analyses were used to examine the association between accelerometer measures and CSF biomarkers, adjusting for age, sex, and other relevant covariates. Results Engagement in moderate PA was associated with higher Aβ42 (P = .008), lower total tau/Aβ42 (P = .006), and lower phosphorylated tau/Aβ42 (P = .030). In contrast, neither light nor vigorous PA was associated with any of the biomarkers. Increased sedentariness was associated with reduced Aβ42 (P = .014). Discussions In this cohort, moderate PA, but not light or vigorous, was associated with a favorable AD biomarker profile, while sedentariness was associated with greater Aβ burden. These findings suggest that a physically active lifestyle may play a protective role against the development of AD.

Alzheimer's disease (AD), including its mild cognitive impairment (MCI) phase that may or may not progress into the AD, is the most ordinary form of dementia. It is extremely important to correctly identify patients during the MCI stage because this is the phase where AD may or may not develop. Thus, it is crucial to predict outcomes during this phase. Thus far, many researchers have worked on only using a single modality of a biomarker for the diagnosis of AD or MCI. Although recent studies show that a combination of one or more different biomarkers may provide complementary information for the diagnosis, it also increases the classification accuracy distinguishing between different groups. In this paper, we propose a novel machine learning-based framework to discriminate subjects with AD or MCI utilizing a combination of four different biomarkers: fluorodeoxyglucose positron emission tomography (FDG-PET), structural magnetic resonance imaging (sMRI), cerebrospinal fluid (CSF) protein levels, and Apolipoprotein-E (APOE) genotype. The Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline dataset was used in this study. In total, there were 158 subjects for whom all four modalities of biomarker were available. Of the 158 subjects, 38 subjects were in the AD group, 82 subjects were in MCI groups (including 46 in MCIc [MCI converted; conversion to AD within 24 months of time period], and 36 in MCIs [MCI stable; no conversion to AD within 24 months of time period]), and the remaining 38 subjects were in the healthy control (HC) group. For each image, we extracted 246 regions of interest (as features) using the Brainnetome template image and NiftyReg toolbox, and later we combined these features with three CSF and two APOE genotype features obtained from the ADNI website for each subject using early fusion technique. Here, a different kernel-based multiclass support vector machine (SVM) classifier with a grid-search method was applied. Before passing the obtained features to the classifier, we have used truncated singular value decomposition (Truncated SVD) dimensionality reduction technique to reduce high dimensional features into a lower-dimensional feature. As a result, our combined method achieved an area under the receiver operating characteristic (AU-ROC) curve of 98.33, 93.59, 96.83, 94.64, 96.43, and 95.24% for AD vs. HC, MCIs vs. MCIc, AD vs. MCIs, AD vs. MCIc, HC vs. MCIc, and HC vs. MCIs subjects which are high relative to single modality results and other state-of-the-art approaches. Moreover, combined multimodal methods have improved the classification performance over the unimodal classification.

Background Statins improve endothelial function, but their effects on arterial stiffness and aortic blood pressure in middle‐aged adults are uncertain. Methods and Results This was a prospective, randomized, double‐blind, placebo‐controlled trial of middle‐aged (40‐72 years old) adults who were randomly assigned to receive simvastatin 40 mg (n=44) or placebo (n=44) daily for 18 months to evaluate impact on dementia‐related biomarkers (primary end points) and measures of vascular health (secondary end points). This analysis focuses on the predetermined secondary end points of changes in central aortic blood pressure, aortic augmentation index, and brachial artery flow‐mediated dilation. Measurements were performed at baseline and after 6, 12, and 18 months. Multivariable models were used to identify predictors of these prespecified vascular end points. Study groups were similar at baseline; low‐density lipoprotein cholesterol declined in the statin group but not in the placebo group (P0.2). After 12 months, augmentation index decreased from baseline in the statin group compared with the placebo group (−2.3% [5.5%] versus 1.2% [5.7%], P=0.007), but by 18 months the response in both groups trend toward baseline (−1.1% [5.8%] versus 0.2% [4.8%], P=0.3). Low‐density lipoprotein cholesterol was not associated with changes in augmentation index at any time point. Conclusions Statin therapy led to a short‐term reduction in augmentation index after 12 months, but this effect did not persist after 18 months despite continued reduction in low‐density lipoprotein cholesterol levels. These findings suggest that statins may have a transient effect on aortic stiffness. Clinical Trial Registration URL: https://www.clinicaltrials.gov/. Unique identifier: NCT00939822.

Mild cognitive impairment (MCI) is a transitional state between the cognitive changes in normal aging and Alzheimer’s disease (AD), which induces abnormalities in specific brain regions. Previous studies showed that paired helical filaments Tau (PHF-Tau) protein is a potential pathogenic protein which may cause abnormal brain function and structure in MCI and AD patients. However, the understanding of the PHF-Tau protein network in MCI patients is limited. In this study, 225 subjects with PHF-Tau Positron Emission Tomography (PET) images were divided into four groups based on whether they carried Apolipoprotein E ε4 (APOE 4) or abnormal cerebrospinal fluid Total-Tau (CSF T-Tau). They are two important pathogenic factors that might cause cognitive function impairment. The four groups were: individuals harboring CSF T-Tau pathology but no APOE 4 (APOE 4−T+); APOE 4 carriers with normal CSF T-Tau (APOE 4+T−); APOE 4 carriers with abnormal CSF T-Tau (APOE 4+T+); and APOE 4 noncarriers with abnormal CSF T-Tau (APOE 4−T−). We explored the topological organization of PHF-Tau networks in these four groups and calculated five kinds of network properties: clustering coefficient, shortest path length, Q value of modularity, nodal centrality and degree. Our findings showed that compared with APOE 4−T− group, the other three groups showed different alterations in the clustering coefficient, shortest path length, Q value of modularity, nodal centrality and degree. Simultaneously, voxel-level analysis was conducted and the results showed that compared with APOE 4−T− group, the other three groups were found increased PHF-Tau distribution in some brain regions. For APOE 4+T+ group, positive correlation was found between the value of PHF-Tau distribution in altered regions and Functional Assessment Questionnaire (FAQ) score. Our results indicated that the effects of APOE 4 and abnormal CSF T-Tau may induce abnormalities of PHF-Tau protein and APOE 4 has a greater impact on PHF-Tau than abnormal CSF T-Tau. Our results may be particularly helpful in uncovering the pathophysiology underlying the cognitive dysfunction in MCI patients.

BackgroundNon-invasive brain stimulation (NIBS) has been widely used to treat mild cognitive impairment (MCI). However, there exists no consensus on the best stimulation sites.ObjectiveTo explore potential stimulation locations for NIBS treatment in patients with MCI, combining meta- and resting state functional connectivity (rsFC) analyses.MethodsThe meta-analysis was conducted to identify brain regions associated with MCI. Regions of interest (ROIs) were extracted based on this meta-analysis. The rsFC analysis was applied to 45 MCI patients to determine brain surface regions that are functionally connected with the above ROIs.ResultsWe found that the dorsolateral prefrontal cortex (DLPFC) and inferior frontal gyrus (IFG) were the overlapping brain regions between our results and those of previous studies. In addition, we recommend that the temporoparietal junction (including the angular gyrus), which was found in both the meta- and rsFC analysis, should be considered in NIBS treatment of MCI. Furthermore, the bilateral orbital prefrontal gyrus, inferior temporal gyrus, medial superior frontal gyrus, and right inferior occipital gyrus may be potential brain stimulation sites for NIBS treatment of MCI.ConclusionOur results provide several potential sites for NIBS, such as the DLFPC and IFG, and may shed light on the locations of NIBS sites in the treatment of patients with MCI.

Collecting multiple modalities of neuroimaging data on the same subject is increasingly becoming the norm in clinical practice and research. Fusing multiple modalities to find related patterns is a challenge in neuroimaging analysis. Canonical correlation analysis (CCA) is commonly used as a symmetric data fusion technique to find related patterns among multiple modalities. In CCA-based data fusion, principal component analysis (PCA) is frequently applied as a preprocessing step to reduce data dimension followed by CCA on dimension-reduced data. PCA, however, does not differentiate between informative voxels from non-informative voxels in the dimension reduction step. Sparse PCA (sPCA) extends traditional PCA by adding sparse regularization that assigns zero weights to non-informative voxels. In this study, sPCA is incorporated into CCA-based fusion analysis and applied on neuroimaging data. A cross-validation method is developed and validated to optimize the parameters in sPCA. Different simulations are carried out to evaluate the improvement by introducing sparsity constraint to PCA. Four fusion methods including sPCA+CCA, PCA+CCA, parallel ICA and sparse CCA were applied on structural and functional magnetic resonance imaging data of mild cognitive impairment subjects and normal controls. Our results indicate that sPCA significantly can reduce the impact of non-informative voxels and lead to improved statistical power in uncovering disease-related patterns by a fusion analysis.

Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification.

Background: Several neurodegeneration (N) metrics using structural MRI are used for the purpose of Alzheimer's disease (AD)-related staging, including hippocampal volume, global atrophy, and an “AD signature” composite consisting of thickness or volumetric estimates derived from regions impacted early in AD. This study sought to determine if less user-intensive estimates of global atrophy and hippocampal volume were equivalent to a thickness-based AD signature from FreeSurfer for defining N across the AD continuum (i.e., individuals who are amyloid-positive (A+)). Methods: Cognitively unimpaired (CU) late middle-aged and older adults, as well as A+ mild cognitive impairment (MCI) and A+ AD dementia individuals, with available CSF and structural MRI scan

In addition to the development of beta amyloid plaques and neurofibrillary tangles, Alzheimer's disease (AD) involves the loss of connecting structures including degeneration of myelinated axons and synaptic connections. However, the extent to which white matter tracts change longitudinally, particularly in the asymptomatic, preclinical stage of AD, remains poorly characterized. In this study we used a novel graph wavelet algorithm to determine the extent to which microstructural brain changes evolve in concert with the development of AD neuropathology as observed using CSF biomarkers. A total of 118 participants with at least two diffusion tensor imaging (DTI) scans and one lumbar puncture for CSF were selected from two observational and longitudinally followed cohorts. CSF was assayed for pathology specific to AD (Aβ42 and phosphorylated-tau), neurodegeneration (total-tau), axonal degeneration (neurofilament light chain protein; NFL), and synaptic degeneration (neurogranin). Tractography was performed on DTI scans to obtain structural connectivity networks with 160 nodes where the nodes correspond to specific brain regions of interest (ROIs) and their connections were defined by DTI metrics (i.e., fractional anisotropy (FA) and mean diffusivity (MD)). For the analysis, we adopted a multi-resolution graph wavelet technique called Wavelet Connectivity Signature (WaCS) which derives higher order representations from DTI metrics at each brain connection. Our statistical analysis showed interactions between the CSF measures and the MRI time interval, such that elevated CSF biomarkers and longer time were associated with greater longitudinal changes in white matter microstructure (decreasing FA and increasing MD). Specifically, we detected a total of 17 fiber tracts whose WaCS representations showed an association between longitudinal decline in white matter microstructure and both CSF p-tau and neurogranin. While development of neurofibrillary tangles and synaptic degeneration are cortical phenomena, the results show that they are also associated with degeneration of underlying white matter tracts, a process which may eventually play a role in the development of cognitive decline and dementia. Keywords: DTI tractography, CSF biomarker, Longitudinal brain connectivity, Alzheimer's disease pathology, Multi-resolution analysis

Abstract Introduction The potential of intra‐individual cognitive variability (IICV) to predict incident mild cognitive impairment (MCI) or Alzheimer's disease (AD) was examined and compared to well‐established neuroimaging and genetic predictors. Methods IICV was estimated using four neuropsychological measures for n = 1324 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants who were cognitively healthy or diagnosed with MCI at baseline. IICV was used to predict time to incident MCI or AD, and compared to hippocampal volume loss and APOE ε4 status via survival analysis. Results In survival analyses, controlling for age, education, baseline diagonosis, and APOE ε4 status, likelihood ratio tests indicate that IICV is associated with time to cognitive status change in the full sample (P

Abstract Introduction Physical activity (PA) is associated with brain health in older adults. However, it is unknown whether the current physical activity recommendations (PAR) impart substantive benefit. The objective of this study was to compare temporal lobe volumes between older adults who met PAR and those who did not. Methods Ninety‐one enrollees from the Wisconsin Registry for Alzheimer's Prevention wore an accelerometer for seven consecutive days to quantify their PA behaviors and underwent a T‐1 anatomic magnetic resonance imaging scan. Participants were categorized as either having met PAR or not based on the US Department of Health and Human Services recommendations of 150 minutes of moderate‐to‐vigorous physical activity per week. Results Participants who met PAR possessed significantly greater inferior (η2P = .050) and anterior (η2P = .055) temporal lobe volumes compared with those who did not (P

Abstract There is a growing interest in understanding how amyloid β (Aβ) accumulation in preclinical Alzheimer's disease relates to brain morphometric measures and cognition. Existing investigations in this area have been primarily conducted in older cognitively normal (CN) individuals. Therefore, not much is known about the associations between Aβ burden, cortical thickness, and cognition in midlife. We examined this question in 109, CN, late to middle‐aged adults (mean age = 60.72 ± 5.65 years) from the Wisconsin Registry for Alzheimer's Prevention. They underwent Pittsburgh Compound B (PiB) and anatomical magnetic resonance (MR) imaging, and a comprehensive cognitive examination. Blinded visual rating of the PiB scans was used to classify the participants as Aβ+ or Aβ−. Cortical thickness measurements were derived from the MR images. The Aβ+ group exhibited significant thinning of the entorhinal cortex and accelerated age‐associated thinning of the parahippocampal gyrus compared with the Aβ− group. The Aβ+ group also had numerically lower, but nonsignificant, test scores on all cognitive measures, and significantly faster age‐associated cognitive decline on measures of Speed & Flexibility, Verbal Ability, and Visuospatial Ability. Our findings suggest that early Aβ aggregation is associated with deleterious changes in brain structure and cognitive function, even in midlife, and that the temporal lag between Aβ deposition and the inception of neurodegenerative/cognitive changes might be narrower than currently thought.

Abstract Background Subjective memory complaints (SMCs) represent an individual's perception of subtle changes in memory in the absence of objective impairment in memory. However, it is not fully known whether persons with SMCs harbor brain alterations related to Alzheimer's disease (AD) or whether they indeed demonstrate poorer cognitive performance. Methods The participants were 261 middle‐age adults (mean age 54.30 years) enrolled in the Wisconsin Registry for Alzheimer's Prevention, a registry of cognitively normal adults at risk of AD. They answered a question pertaining to subjective memory, completed a comprehensive neuropsychological examination, and subsequently underwent a volumetric magnetic resonance imaging scan. Cortical thickness measurements were derived from 10 a priori regions of interest involved in AD. Analyses of covariance were conducted to investigate the group differences in cortical thickness and neuropsychological measures. Results Compared with individuals without SMCs, those with SMCs had significant cortical thinning in the entorhinal, fusiform, posterior cingulate, and inferior parietal cortices and significantly reduced amygdala volume. Similarly, those with SMCs had significantly lower test scores on measures of Immediate Memory, Verbal Learning & Memory, and Verbal Ability. Additional adjustment for depressive symptoms (which differed between the groups) attenuated only the findings for the entorhinal cortex (P = .061) and Verbal Ability (P = .076). Conclusion At‐risk, cognitively healthy individuals with SMCs exhibit cortical thinning in brain regions affected by AD and poorer performance on objective memory tests. These findings suggest that, in some individuals, SMCs might represent the earliest stages of AD.