Alzheimer incidence and prevalence with and without asthma: A Medicare cohort study.

BACKGROUND: International data suggest that asthma, like other inflammatory diseases, might increase Alzheimer disease (AD) risk. OBJECTIVE: We sought to explore risk pathways and future mitigation strategies by comparing diagnostic claims-based AD incidence and prevalence among US patients with asthma with those without asthma. METHODS: This cohort study included a national Medicare 20% random sample (2013-2015). Adult patients with asthma with more than 12 months continuous Medicare were compared with subjects without asthma overall and as matched. Asthma was defined by 1 inpatient or 2 outpatient codes for asthma. The main outcomes were 2-year incident or prevalent AD defined by International Classification of Diseases, Ninth Revision code 331.0 or Tenth Revision code G30.0, G30.1, G30.8, or G30.9. RESULTS: Among 5,460,732 total beneficiaries, 678,730 patients were identified with baseline asthma and more often identified as Black or Hispanic, were Medicaid eligible, or resided in a highly disadvantaged neighborhood than those without asthma. Two-year incidence of AD was 1.4% with asthma versus 1.1% without asthma; prevalence was 7.8% versus 5.4% (both P ≤ .001). Per 100,000 patients over 2 years, 303 more incident AD diagnoses occurred in those with asthma, with 2,425 more prevalent cases (P < .001). Multivariable models showed that asthma had greater odds of 2-year AD incidence (adjusted odds ratio, 1.33 [95% CI, 1.29-1.36]; matched 1.2 [95% CI, 1.17-1.24]) and prevalence (adjusted odds ratio, 1.48 [95% CI, 1.47-1.50]; matched 1.25 [95% CI, 1.22-1.27]). CONCLUSIONS: Asthma was associated with 20% to 33% increased 2-year incidence and 25% to 48% increased prevalence of claims-based AD in this nationally representative US sample. Future research should investigate risk pathways of underlying comorbidities and social determinants as well as whether there are potential asthma treatments that may preserve brain health.

Circadian-Dependent Intermittent Fasting Influences Ischemic Tolerance and Dendritic Spine Remodeling.

BACKGROUND: Preconditioning by intermittent fasting is linked to improved cognition and motor function, and enhanced recovery after stroke. Although the duration of fasting was shown to elicit different levels of neuroprotection after ischemic stroke, the impact of time of fasting with respect to the circadian cycles remains unexplored. METHODS: Cohorts of mice were subjected to a daily 16-hour fast, either during the dark phase (active-phase intermittent fasting) or the light phase (inactive-phase intermittent fasting) or were fed ad libitum. Following a 6-week dietary regimen, mice were subjected to transient focal cerebral ischemia and underwent behavioral functional assessment. Brain samples were collected for RNA sequencing and histopathologic analyses. RESULTS: Active-phase intermittent fasting cohort exhibited better poststroke motor and cognitive recovery as well as reduced infarction, in contrast to inactive-phase intermittent fasting cohort, when compared with ad libitum cohort. In addition, protection of dendritic spine density/morphology and increased expression of postsynaptic density protein-95 were observed in the active-phase intermittent fasting. CONCLUSIONS: These findings indicate that the time of daily fasting is an important factor in inducing ischemic tolerance by intermittent fasting.

CSF Biomarkers in Longitudinal Alzheimer Disease Cohorts: Pre-Analytic Challenges.

BACKGROUND: The sensitivity of amyloid to pre-analytic factors complicates cerebrospinal fluid (CSF) diagnostics for Alzheimer disease. We report reliability and validity evidence for automated immunoassays from frozen and fresh CSF samples in an ongoing, single-site research program. METHODS: CSF samples were obtained from 2 Wisconsin cohorts (1256 measurements; 727 participants). Levels of amyloid beta 1-42 (Aß42), phosphorylated tau 181 (pTau181), and total tau (tTau) were obtained using an Elecsys cobas e 601 platform. Repeatability and fixed effects of storage tube type, extraction method, and freezing were assessed via mixed models. Concordance with amyloid positron emission tomography (PET) was investigated with 238 participants having a temporally proximal PET scan. RESULTS: Repeatability was high with intraclass correlation (ICC) ≥0.9, but tube type strongly affected measurements. Discriminative accuracy for PET amyloid positivity was strong across tube types (area under the curve [AUC]: Aß42, 0.87; pTau181Aß42 , 0.96), although optimal thresholds differed. CONCLUSIONS: Under real-world conditions, the Elecsys platform had high repeatability. However, strong effects of pre-analytic factors suggest caution in drawing longitudinal inferences.

Poor self-rated health is associated with faster cognitive decline and greater small vessel disease in older adults with type 2 diabetes.

OBJECTIVE: Self-rated health (SRH) is a predictor for poor health outcomes and cognition. Older adults with type 2 diabetes mellitus (T2D) have multi-morbidity and greater cognitive impairment. In the present study we investigated the association of SRH with cognitive decline and brain pathology in older adults with T2D. METHODS: Participants (n = 1122) were from the Israel Diabetes and Cognitive Decline study, and SRH was categorised as low (n = 202), moderate (n = 400) or high (n = 520). Cognition was measured by four cognitive domains: episodic memory, executive functions, language, and attention/working memory. Global cognition was the average of the cognitive domains. Statistical models adjusted for sociodemographic, cardiovascular, and clinical variables. In a randomly selected subsample (n = 230) that had magnetic resonance imaging, we examined relationships between baseline SRH and brain characteristics (white matter hyperintensities [WMHs], hippocampal, and total grey matter [GM] volumes). RESULTS: Low SRH was associated with a decline in executive functions, which accelerated over time when compared to high SRH (est = -0.0036; p = <0.001). Compared to high SRH, low SRH was associated with a faster decline in global cognition (est = -0.0024; p = 0.009). Low SRH at baseline was associated with higher volumes of WMHs (est = 9.8420; p < 0.0008). SRH was not associated with other cognitive domains, or with hippocampal and total GM. CONCLUSIONS: Low SRH is associated with cognitive decline in T2D older adults and may serve as a risk assessment. WMHs may represent an underlying mechanism.

Association between military service and Alzheimer's disease neuropathology at autopsy.

INTRODUCTION: Anti-amyloid therapies are at the forefront of efforts to treat Alzheimer's disease (AD). Identifying amyloid risk factors may aid screening and intervention strategies. While veterans face increased exposure to risk factors, whether they face a greater neuropathologic amyloid burden is not well understood. METHODS: Male decedents donating to two Alzheimer's Disease Research Center (ADRC) brain banks from 1986 to 2018 with categorized neuritic plaque density and neurofibrillary tangles (n = 597) were included. Using generalized ordered logistic regression we modeled each outcome's association with military history adjusting for age and death year. RESULTS: Having served in the military (60% of sample) is associated with post mortem neuritic amyloid plaque (for each comparison of higher to lower C scores OR = 1.26; 95% confidence interval [CI] = 1.06-1.49) and tau pathology (B score OR = 1.10; 95% CI = 1.08-1.12). DISCUSSION: This is the first study, to our knowledge, finding increased levels of verified AD neuropathology in those with military service. Targeted veteran AD therapies is a pressing need.

Deriving life-course residential histories in brain bank cohorts: A feasibility study.

INTRODUCTION: The exposome is theorized to interact with biological mechanisms to influence risk for Alzheimer's disease but is not well-integrated into existing Alzheimer's Disease Research Center (ADRC) brain bank data collection. METHODS: We apply public data tracing, an iterative, dual abstraction and validation process rooted in rigorous historic archival methods, to develop life-course residential histories for 1254 ADRC decedents. RESULTS: The median percentage of the life course with an address is 78.1% (IQR 24.9); 56.5% of the sample has an address for at least 75% of their life course. Archivists had 89.7% agreement at the address level. This method matched current residential survey methodology 97.4% on average. DISCUSSION: This novel method demonstrates feasibility, reproducibility, and rigor for historic data collection. To our knowledge, this is the first study to show that public data tracing methods for brain bank decedent residential history development can be used to better integrate the social exposome with biobank specimens. HIGHLIGHTS: Public data tracing compares favorably to survey-based residential history. Public data tracing is feasible and reproducible between archivists. Archivists achieved 89.7% agreement at the address level. This method identifies residences for nearly 80% of life-years, on average. This novel method enables brain banks to add social characterizations.

Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge.

Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods.

Genetic and environmental influence on resting state networks in young male and female adults: a cartographer mapping study.

We propose a unique, minimal assumption, approach based on variance analyses (compared with standard approaches) to investigate genetic influence on individual differences on the functional connectivity of the brain using 65 monozygotic and 65 dizygotic healthy young adult twin pairs' low-frequency oscillation resting state functional Magnetic Resonance Imaging (fMRI) data from the Human Connectome Project. Overall, we found high number of genetically-influenced functional (GIF) connections involving posterior to posterior brain regions (occipital/temporal/parietal) implicated in low-level processes such as vision, perception, motion, categorization, dorsal/ventral stream visuospatial, and long-term memory processes, as well as high number across midline brain regions (cingulate) implicated in attentional processes, and emotional responses to pain. We found low number of GIF connections involving anterior to anterior/posterior brain regions (frontofrontal > frontoparietal, frontotemporal, frontooccipital) implicated in high-level processes such as working memory, reasoning, emotional judgment, language, and action planning. We found very low number of GIF connections involving subcortical/noncortical networks such as basal ganglia, thalamus, brainstem, and cerebellum. In terms of sex-specific individual differences, individual differences in males were more genetically influenced while individual differences in females were more environmentally influenced in terms of the interplay of interactions of Task positive networks (brain regions involved in various task-oriented processes and attending to and interacting with environment), extended Default Mode Network (a central brain hub for various processes such as internal monitoring, rumination, and evaluation of self and others), primary sensorimotor systems (vision, audition, somatosensory, and motor systems), and subcortical/noncortical networks. There were >8.5-19.1 times more GIF connections in males than females. These preliminary (young adult cohort-specific) findings suggest that individual differences in the resting state brain may be more genetically influenced in males and more environmentally influenced in females; furthermore, standard approaches may suggest that it is more substantially nonadditive genetics, rather than additive genetics, which contribute to the differences in sex-specific individual differences based on this young adult (male and female) specific cohort. Finally, considering the preliminary cohort-specific results, based on standard approaches, environmental influences on individual differences may be substantially greater than that of genetics, for either sex, frontally and brain-wide. [Correction added on 10 May 2023, after first online publication: added: functional Magnetic Resonance Imaging. Added: individual differences in, twice. Added statement between furthermore … based on standard approaches.].

Behavioral and Brain Correlates of Emotional Distress in Older Adults During COVID-19 Quarantine.

COVID-19 led to unprecedented lockdowns and changes in older adults' lives, especially those with type 2 diabetes who have high risk of complications and mortality. We investigated the associations of cognitive and motor function and gray matter volumes (GMVs) with COVID-19 lockdown-related emotional distress of type 2 diabetes older adults, participating in the Israel Diabetes and Cognitive Decline Study. We administered a questionnaire to obtain information about anxiety, depression, general well-being, and optimism during a mandated lockdown. Lower grip strength before lockdown was associated with increased sadness, anxiety, and less optimism. Slower gait speed was associated with greater sadness. Lower GMV was related to greater anxiety during the lockdown when compared with anxiety levels before the COVID-19 outbreak. Yet, global cognition was not associated with any emotional distress measure. These results support the role of good motor function on emotional well-being during acute stress and GMV as a potential underlying mechanism.

Neuroimaging and biomarker evidence of neurodegeneration in asthma.

BACKGROUND: Epidemiologic studies have shown that Alzheimer's disease (AD) and related dementias (ADRD) are seen more frequently with asthma, especially with greater asthma severity or exacerbation frequency. OBJECTIVE: To examine the changes in brain structure that may underlie this phenomenon, we examined diffusion-weighted magnetic resonance imaging (dMRI) and blood-based biomarkers of AD (phosphorylated tau 181, p-Tau181), neurodegeneration (neurofilament light chain, NfL), and glial activation (glial fibrillary acidic protein, GFAP). METHODS: dMRI data were obtained in 111 individuals with asthma, ranging in disease severity from mild to severe, and 135 healthy controls. Regression analyses were used to test the relationships between asthma severity and neuroimaging measures, as well as AD pathology, neurodegeneration, and glial activation, indexed by plasma p-Tau181, NfL, and GFAP, respectively. Additional relationships were tested with cognitive function. RESULTS: Asthma participants had widespread and large-magnitude differences in several dMRI metrics, which were indicative of neuroinflammation and neurodegeneration, and which were robustly associated with GFAP and, to a lesser extent, NfL. The AD biomarker p-Tau181 was only minimally associated with neuroimaging outcomes. Further, asthma severity was associated with deleterious changes in neuroimaging outcomes, which in turn were associated with slower processing speed, a test of cognitive performance. CONCLUSIONS: Asthma, particularly when severe, is associated with characteristics of neuroinflammation and neurodegeneration, and may be a potential risk factor for neural injury and cognitive dysfunction. There is a need to determine how asthma may affect brain health and whether treatment directed toward characteristics of asthma associated with these risks can mitigate these effects.

Neuropathology-based APOE genetic risk score better quantifies Alzheimer's risk.

INTRODUCTION: Apolipoprotein E (APOE) ε4-carrier status or ε4 allele count are included in analyses to account for the APOE genetic effect on Alzheimer's disease (AD); however, this does not account for protective effects of APOE ε2 or heterogeneous effect of ε2, ε3, and ε4 haplotypes. METHODS: We leveraged results from an autopsy-confirmed AD study to generate a weighted risk score for APOE (APOE-npscore). We regressed cerebrospinal fluid (CSF) amyloid and tau biomarkers on APOE variables from the Wisconsin Registry for Alzheimer's Prevention (WRAP), Wisconsin Alzheimer's Disease Research Center (WADRC), and Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS: The APOE-npscore explained more variance and provided a better model fit for all three CSF measures than APOE ε4-carrier status and ε4 allele count. These findings were replicated in ADNI and observed in subsets of cognitively unimpaired (CU) participants. DISCUSSION: The APOE-npscore reflects the genetic effect on neuropathology and provides an improved method to account for APOE in AD-related analyses.

Large-scale proteome and metabolome analysis of CSF implicates altered glucose and carbon metabolism and succinylcarnitine in Alzheimer's disease.

INTRODUCTION: A hallmark of Alzheimer's disease (AD) is the aggregation of proteins (amyloid beta [A] and hyperphosphorylated tau [T]) in the brain, making cerebrospinal fluid (CSF) proteins of particular interest. METHODS: We conducted a CSF proteome-wide analysis among participants of varying AT pathology (n = 137 participants; 915 proteins) with nine CSF biomarkers of neurodegeneration and neuroinflammation. RESULTS: We identified 61 proteins significantly associated with the AT category (P < 5.46 × 10-5 ) and 636 significant protein-biomarker associations (P < 6.07 × 10-6 ). Proteins from glucose and carbon metabolism pathways were enriched among amyloid- and tau-associated proteins, including malate dehydrogenase and aldolase A, whose associations with tau were replicated in an independent cohort (n = 717). CSF metabolomics identified and replicated an association of succinylcarnitine with phosphorylated tau and other biomarkers. DISCUSSION: These results implicate glucose and carbon metabolic dysregulation and increased CSF succinylcarnitine levels with amyloid and tau pathology in AD. HIGHLIGHTS: Cerebrospinal fluid (CSF) proteome enriched for extracellular, neuronal, immune, and protein processing. Glucose/carbon metabolic pathways enriched among amyloid/tau-associated proteins. Key glucose/carbon metabolism protein associations independently replicated. CSF proteome outperformed other omics data in predicting amyloid/tau positivity. CSF metabolomics identified and replicated a succinylcarnitine-phosphorylated tau association.

Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI.

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset. Macaque brains that have received both tracer injections and ex vivo dMRI at high spatial and angular resolution allow a comprehensive, quantitative assessment of tractography accuracy on state-of-the-art dMRI acquisition schemes. We find that, when analysis methods are carefully optimized, the HCP scheme can achieve similar accuracy as a more time-consuming, Cartesian-grid scheme. Importantly, we show that simple pre- and post-processing strategies can improve the accuracy and robustness of many tractography methods. Finally, we find that fiber configurations that go beyond crossing (e.g., fanning, branching) are the most challenging for tractography. The IronTract Challenge remains open and we hope that it can serve as a valuable validation tool for both users and developers of dMRI analysis methods.

Biomarkers for Alzheimer's disease-preparing for a new era of disease-modifying therapies.

Clinical trial results presented in 2019 suggest that antibody-based removal of cerebral amyloid ß (Aß) plaques may possibly clear tau tangles and modestly slow cognitive decline in symptomatic Alzheimer's disease (AD). Although regulatory approval of this approach is still pending, preparing the healthcare system for the advent of disease-modifying therapies against AD is imperative. In particular, it will be necessary to identify the most suitable biomarkers to facilitate appropriate treatment of AD. Here, we give an update on recent developments in fluid and imaging biomarkers for AD-related pathologies and discuss potential approaches that could be adopted to screen for and clarify the underlying pathology in people seeking medical advice because of cognitive symptoms. We succinctly review recent data regarding biomarkers for Aß and tau pathology, neurodegeneration, synaptic dysfunction, and inflammation, highlight the need for further research into common copathologies, and suggest how different biomarkers could be used (most likely in combination) to facilitate the development and clinical implementation of novel drug candidates against AD.

Alzheimer's disease biomarkers in Black and non-Hispanic White cohorts: A contextualized review of the evidence.

Black Americans are disproportionately affected by dementia. To expand our understanding of mechanisms of this disparity, we look to Alzheimer's disease (AD) biomarkers. In this review, we summarize current data, comparing the few studies presenting these findings. Further, we contextualize the data using two influential frameworks: the National Institute on Aging-Alzheimer's Association (NIA-AA) Research Framework and NIA's Health Disparities Research Framework. The NIA-AA Research Framework provides a biological definition of AD that can be measured in vivo. However, current cut-points for determining pathological versus non-pathological status were developed using predominantly White cohorts-a serious limitation. The NIA's Health Disparities Research Framework is used to contextualize findings from studies identifying racial differences in biomarker levels, because studying biomakers in isolation cannot explain or reduce inequities. We offer recommendations to expand study beyond initial reports of racial differences. Specifically, life course experiences associated with racialization and commonly used study enrollment practices may better account for observations than exclusively biological explanations.

Interaction of amyloid and tau on cortical microstructure in cognitively unimpaired adults.

INTRODUCTION: Neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion-weighted imaging (DWI) model, may be useful for detecting early cortical microstructural alterations in Alzheimer's disease prior to cognitive impairment. METHODS: Using neuroimaging (NODDI and T1-weighted magnetic resonance imaging [MRI]) and cerebrospinal fluid (CSF) biomarker data (measured using Elecsys® CSF immunoassays) from 219 cognitively unimpaired participants, we tested the main and interactive effects of CSF amyloid beta (Aß)42 /Aß40 and phosphorylated tau (p-tau) on cortical NODDI metrics and cortical thickness, controlling for age, sex, and apolipoprotein E ε4. RESULTS: We observed a significant CSF Aß42 /Aß40 × p-tau interaction on cortical neurite density index (NDI), but not orientation dispersion index or cortical thickness. The directionality of these interactive effects indicated: (1) among individuals with lower CSF p-tau, greater amyloid burden was associated with higher cortical NDI; and (2) individuals with greater amyloid and p-tau burden had lower cortical NDI, consistent with cortical neurodegenerative changes. DISCUSSION: NDI is a particularly sensitive marker for early cortical changes that occur prior to gross atrophy or development of cognitive impairment.

Cortical Microstructural Alterations in Mild Cognitive Impairment and Alzheimer's Disease Dementia.

In Alzheimer's disease (AD), neurodegenerative processes are ongoing for years prior to the time that cortical atrophy can be reliably detected using conventional neuroimaging techniques. Recent advances in diffusion-weighted imaging have provided new techniques to study neural microstructure, which may provide additional information regarding neurodegeneration. In this study, we used neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion model, in order to investigate cortical microstructure along the clinical continuum of mild cognitive impairment (MCI) and AD dementia. Using gray matter-based spatial statistics (GBSS), we demonstrated that neurite density index (NDI) was significantly lower throughout temporal and parietal cortical regions in MCI, while both NDI and orientation dispersion index (ODI) were lower throughout parietal, temporal, and frontal regions in AD dementia. In follow-up ROI analyses comparing microstructure and cortical thickness (derived from T1-weighted MRI) within the same brain regions, differences in NODDI metrics remained, even after controlling for cortical thickness. Moreover, for participants with MCI, gray matter NDI-but not cortical thickness-was lower in temporal, parietal, and posterior cingulate regions. Taken together, our results highlight the utility of NODDI metrics in detecting cortical microstructural degeneration that occurs prior to measurable macrostructural changes and overt clinical dementia.

An examination of a novel multipanel of CSF biomarkers in the Alzheimer's disease clinical and pathological continuum.

INTRODUCTION: This study examines the utility of a multipanel of cerebrospinal fluid (CSF) biomarkers complementing Alzheimer's disease (AD) biomarkers in a clinical research sample. We compared biomarkers across groups defined by clinical diagnosis and pTau181 /Aß42 status (+/-) and explored their value in predicting cognition. METHODS: CSF biomarkers amyloid beta (Aß)42 , pTau181 , tTau, Aß40 , neurogranin, neurofilament light (NfL), α-synuclein, glial fibrillary acidic protein (GFAP), chitinase-3-like protein 1 (YKL-40), soluble triggering receptor expressed on myeloid cells 2 (sTREM2), S100 calcium binding protein B (S100B), and interleukin 6 (IL6), were measured with the NeuroToolKit (NTK) for 720 adults ages 40 to 93 years (mean age = 63.9 years, standard deviation [SD] = 9.0; 50 with dementia; 54 with mild cognitive impairment [MCI], 616 unimpaired). RESULTS: Neurodegeneration and glial activation biomarkers were elevated in pTau181 /Aß42 + MCI/dementia participants relative to all pTau181 /Aß42 - participants. Neurodegeneration biomarkers increased with clinical severity among pTau181 /Aß42 + participants and predicted worse cognitive performance. Glial activation biomarkers were unrelated to cognitive performance. DISCUSSION: The NTK contains promising markers that improve the pathophysiological characterization of AD. Neurodegeneration biomarkers beyond tTau improved statistical prediction of cognition and disease stages.

Higher BMI is associated with smaller regional brain volume in older adults with type 2 diabetes.

AIMS/HYPOTHESIS: There are established relationships between adiposity (obesity) and higher dementia risk, faster cognitive decline and associated neural injury. Type 2 diabetes is strongly linked to greater adiposity and has been consistently associated with neural injury and poor cognitive outcomes. However, although obesity is a major cause of type 2 diabetes, there is limited evidence on the association of adiposity with brain atrophy among individuals with type 2 diabetes. METHODS: We examined the association of BMI (a measure of adiposity), and of long-term trajectories of BMI (three empirically identified groups of trajectories-'normal', 'overweight' and 'obese'-using SAS macro PROC TRAJ), with regional brain volume, in a sample of older individuals (aged 64-84) with type 2 diabetes participating in the Israel Diabetes and Cognitive Decline Study (n = 198). RESULTS: Using linear regression, we found that greater BMI was associated with smaller volumes of the inferior frontal gyrus (IFG) (r = -0.25, p = 0.001) and the middle temporal gyrus (r = -0.19; p = 0.010) after adjusting for sociodemographic covariates and total intracranial volume. In addition, there were significant differences between BMI trajectory groups in IFG volume (F = 4.34, p = 0.014), such that a long-term trajectory of obesity was associated with a smaller volume. Additional adjustment for cardiovascular and diabetes-related potential confounders did not substantively alter the results. There were no associations of adiposity with superior frontal gyrus, middle frontal gyrus or total grey matter volumes. CONCLUSIONS/INTERPRETATION: In older adults with type 2 diabetes, long-term adiposity may have a detrimental impact on volume of brain regions relevant to cognitive functioning. Further studies to identify the underlying mechanisms are warranted. Graphical abstract.

Extracellular vesicle biomarkers of Alzheimer's disease associated with sub-clinical cognitive decline in late middle age.

INTRODUCTION: Neuronal extracellular vesicle (nEV) tau and insulin signaling biomarkers may detect preclinical Alzheimer's disease and age-associated cognitive decline. METHODS: This case-control study used repeated serum samples from 73 cognitively declining and 73 stable Wisconsin Registry for Alzheimer's Prevention participants (62.4 ± 6.3 years old). We immunocaptured nEVs; measured tau and insulin signaling biomarkers; and examined biomarker differences by group, their performance in group classification in training and test datasets (97, 49 individuals, respectively), and whether they predict cognitive performance change. RESULTS: Declining compared to stable individuals showed higher baseline total, p231-, and p181-tau with older age and higher annualized change for p-IR and p-IGF-1R. Combining biomarkers classified decliners with 94% area under the curve (AUC), 86.0% sensitivity and 86.7% specificity, in training data, and 75% AUC, 71.4% sensitivity, and 77.3% specificity, in test data. Insulin biomarkers predicted cognitive performance change prospectively. DISCUSSION: Combining nEV biomarkers can identify individuals with age-associated cognitive decline.