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Objective To investigate Tau pathology using multimodal biomarkers of neurodegeneration and neurocognition in participants with myotonic dystrophy type 1 (DM1). Methods We recruited twelve participants with DM1 and, for comparison, two participants with Alzheimer’s Disease (AD). Participants underwent cognitive screening and social cognition testing using the Dépistage Cognitif de Québec (DCQ), among other tests. Biomarkers included Tau PET with [18F]-AV-1451, CSF (Aβ, Tau, phospho-Tau), and plasma (Aβ, Tau, Nf-L, GFAP) studies. Results Of the twelve DM1 participants, seven completed the full protocol (Neurocognition 11/12; PET 7/12, CSF 9/12, plasma 12/12). Three DM1 participants were cognitively impaired (CI). On average, CI DM1 participants had lower scores on the DCQ compared to cognitively unimpaired (CU) DM1 participants (75.5/100 vs. 91.4/100) and were older (54 vs. 44 years old) but did not differ in years of education (11.3 vs. 11.1). The majority (6/7) of DM1 participants had no appreciable PET signal. Only one of the CI participants presented with elevated Tau PET SUVR in bilateral medial temporal lobes. This participant was the eldest and most cognitively impaired, and had the lowest CSF Aβ 1-42 and the highest CSF Tau levels, all suggestive of co-existing AD. CSF Tau and phospho-Tau levels were higher in the 3 CI compared to CU DM1 participants, but with a mean value lower than that typically observed in AD. Nf-L and GFAP were elevated in most DM1 participants (9/11 and 8/11, respectively). Finally, CSF phospho-Tau was significantly correlated with plasma Nf-L concentrations. Conclusions and relevance We observed heterogenous cognitive and biomarker profiles in individuals with DM1. While some participants presented with abnormal PET and/or CSF Tau, these patterns were highly variable and only present in a small subset. Although DM1 may indeed represent a non-AD Tauopathy, the Tau-PET tracer used in this study was unable to detect an in vivo Tau DM1 signature in this small cohort. Interestingly, most DM1 participants presented with elevated plasma Nf-L and GFAP levels, suggestive of other, possibly related, central brain alterations which motivate further research. This pioneering study provides novel insights towards the potential relationship between biomarkers and neurocognitive deficits commonly seen in DM1.

To investigate Tau pathology using multimodal biomarkers of neurodegeneration and neurocognition in participants with myotonic dystrophy type 1 (DM1).We recruited twelve participants with DM1 and, for comparison, two participants with Alzheimer's Disease (AD). Participants underwent cognitive screening and social cognition testing using the Dépistage Cognitif de Québec (DCQ), among other tests. Biomarkers included Tau PET with [18F]-AV-1451, CSF (Aβ, Tau, phospho-Tau), and plasma (Aβ, Tau, Nf-L, GFAP) studies.Of the twelve DM1 participants, seven completed the full protocol (Neurocognition 11/12; PET 7/12, CSF 9/12, plasma 12/12). Three DM1 participants were cognitively impaired (CI). On average, CI DM1 participants had lower scores on the DCQ compared to cognitively unimpaired (CU) DM1 participants (75.5/100 vs. 91.4/100) and were older (54 vs. 44 years old) but did not differ in years of education (11.3 vs. 11.1). The majority (6/7) of DM1 participants had no appreciable PET signal. Only one of the CI participants presented with elevated Tau PET SUVR in bilateral medial temporal lobes. This participant was the eldest and most cognitively impaired, and had the lowest CSF Aβ 1-42 and the highest CSF Tau levels, all suggestive of co-existing AD. CSF Tau and phospho-Tau levels were higher in the 3 CI compared to CU DM1 participants, but with a mean value lower than that typically observed in AD. Nf-L and GFAP were elevated in most DM1 participants (9/11 and 8/11, respectively). Finally, CSF phospho-Tau was significantly correlated with plasma Nf-L concentrations.We observed heterogenous cognitive and biomarker profiles in individuals with DM1. While some participants presented with abnormal PET and/or CSF Tau, these patterns were highly variable and only present in a small subset. Although DM1 may indeed represent a non-AD Tauopathy, the Tau-PET tracer used in this study was unable to detect an in vivo Tau DM1 signature in this small cohort. Interestingly, most DM1 participants presented with elevated plasma Nf-L and GFAP levels, suggestive of other, possibly related, central brain alterations which motivate further research. This pioneering study provides novel insights towards the potential relationship between biomarkers and neurocognitive deficits commonly seen in DM1.

OBJECTIVES To measure the burden of delirium in older adults with or without Alzheimer disease or related disorders (ADRDs). DESIGN Prospective, observational cohort. SETTING Inpatient hospital and study participants' homes. PARTICIPANTS A subset (n = 267) of older medical and surgical patients and their caregivers enrolled in the Better Assessment of Illness study. MEASUREMENTS Delirium burden was measured using the DEL-B instrument (range = 0-40, with higher scores indicating greater burden) in caregivers (DEL-B-C) and patients 1 month after hospitalization. Severity of cognitive impairment (Montreal Cognitive Assessment [MoCA]), delirium presence (Confusion Assessment Method [CAM]), and delirium severity (CAM-Severity [CAM-S]) were measured during hospitalization and at 1-month follow-up. ADRD diagnosis was determined by a clinical consensus process. RESULTS For patients with (n = 56) and without (n = 211) ADRD, both DEL-B instruments had good internal consistency. DEL-B-C scores had a median (interquartile range) among caregivers of patients with and without ADRD of 9 (5-15) and 5 (1-11), respectively (P

Editor’s PerspectiveWhat We Already Know about This TopicWhat This Article Tells Us That Is NewBackgroundPostoperative delirium and postoperative cognitive dysfunction share risk factors and may co-occur, but their relationship is not well established. The primary goals of this study were to describe the prevalence of postoperative cognitive dysfunction and to investigate its association with in-hospital delirium. The authors hypothesized that delirium would be a significant risk factor for postoperative cognitive dysfunction during follow-up.MethodsThis study used data from an observational study of cognitive outcomes after major noncardiac surgery, the Successful Aging after Elective Surgery study. Postoperative delirium was evaluated each hospital day with confusion assessment method–based interviews supplemented by chart reviews. Postoperative cognitive dysfunction was determined using methods adapted from the International Study of Postoperative Cognitive Dysfunction. Associations between delirium and postoperative cognitive dysfunction were examined at 1, 2, and 6 months.ResultsOne hundred thirty-four of 560 participants (24%) developed delirium during hospitalization. Slightly fewer than half (47%, 256 of 548) met the International Study of Postoperative Cognitive Dysfunction-defined threshold for postoperative cognitive dysfunction at 1 month, but this proportion decreased at 2 months (23%, 123 of 536) and 6 months (16%, 85 of 528). At each follow-up, the level of agreement between delirium and postoperative cognitive dysfunction was poor (kappa less than .08) and correlations were small (r less than .16). The relative risk of postoperative cognitive dysfunction was significantly elevated for patients with a history of postoperative delirium at 1 month (relative risk = 1.34; 95% CI, 1.07–1.67), but not 2 months (relative risk = 1.08; 95% CI, 0.72–1.64), or 6 months (relative risk = 1.21; 95% CI, 0.71–2.09).ConclusionsDelirium significantly increased the risk of postoperative cognitive dysfunction in the first postoperative month; this relationship did not hold in longer-term follow-up. At each evaluation, postoperative cognitive dysfunction was more common among patients without delirium. Postoperative delirium and postoperative cognitive dysfunction may be distinct manifestations of perioperative neurocognitive deficits.

Introduction Our goal was to determine if features of surgical patients, easily obtained from the medical chart or brief interview, could be used to predict those likely to experience more rapid cognitive decline following surgery. Methods We analyzed data from an observational study of 560 older adults (≥70 years) without dementia undergoing major elective non‐cardiac surgery. Cognitive decline was measured using change in a global composite over 2 to 36 months following surgery. Predictive features were identified as variables readily obtained from chart review or a brief patient assessment. We developed predictive models for cognitive decline (slope) and predicting dichotomized cognitive decline at a clinically determined cut. Results In a hold‐out testing set, the regularized regression predictive model achieved a root mean squared error (RMSE) of 0.146 and a model r‐square (R2) of .31. Prediction of “rapid” decliners as a group achieved an area under the curve (AUC) of .75. Conclusion Some of our models could predict persons with increased risk for accelerated cognitive decline with greater accuracy than relying upon chance, and this result might be useful for stratification of surgical patients for inclusion in future clinical trials.

BACKGROUND: Our objective was to assess the performance of machine learning methods to predict post-operative delirium using a prospective clinical cohort. METHODS: We analyzed data from an observational cohort study of 560 older adults (≥ 70 years) without dementia undergoing major elective non-cardiac surgery. Post-operative delirium was determined by the Confusion Assessment Method supplemented by a medical chart review (N = 134, 24%). Five machine learning algorithms and a standard stepwise logistic regression model were developed in a training sample (80% of participants) and evaluated in the remaining hold-out testing sample. We evaluated three overlapping feature sets, restricted to variables that are readily available or minimally burdensome to collect in clinical settings, including interview and medical record data. A large feature set included 71 potential predictors. A smaller set of 18 features was selected by an expert panel using a consensus process, and this smaller feature set was considered with and without a measure of pre-operative mental status. RESULTS: The area under the receiver operating characteristic curve (AUC) was higher in the large feature set conditions (range of AUC, 0.62–0.71 across algorithms) versus the selected feature set conditions (AUC range, 0.53–0.57). The restricted feature set with mental status had intermediate AUC values (range, 0.53–0.68). In the full feature set condition, algorithms such as gradient boosting, cross-validated logistic regression, and neural network (AUC = 0.71, 95% CI 0.58–0.83) were comparable with a model developed using traditional stepwise logistic regression (AUC = 0.69, 95% CI 0.57–0.82). Calibration for all models and feature sets was poor. CONCLUSIONS: We developed machine learning prediction models for post-operative delirium that performed better than chance and are comparable with traditional stepwise logistic regression. Delirium proved to be a phenotype that was difficult to predict with appreciable accuracy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11606-020-06238-7) contains supplementary material, which is available to authorized users.

Highlights • The relationship between surgery, neuroinflammation, and delirium remains unclear. • [11C]PBR28 positron emission tomography (PET) was used to image neuroinflammation. • Patients showed a global reduction of [11C]PBR28 binding one month after surgery. • [11C]PBR28 binding was not related to delirium or other markers of inflammation. • Post-operative reduction in [11C]PBR28 binding may reflect neuroimmune suppression., Major surgery is associated with a systemic inflammatory cascade that is thought, in some cases, to contribute to transient and/or sustained cognitive decline, possibly through neuroinflammatory mechanisms. However, the relationship between surgery, peripheral and central nervous system inflammation, and post-operative cognitive outcomes remains unclear in humans, primarily owing to limitations of in vivo biomarkers of neuroinflammation which vary in sensitivity, specificity, validity, and reliability. In the present study, [11C]PBR28 positron emission tomography, cerebrospinal fluid (CSF), and blood plasma biomarkers of inflammation were assessed pre-operatively and 1-month post-operatively in a cohort of patients (N = 36; 30 females; ≥70 years old) undergoing major orthopedic surgery under spinal anesthesia. Delirium incidence and severity were evaluated daily during hospitalization. Whole-brain voxel-wise and regions-of-interest analyses were performed to determine the magnitude and spatial extent of changes in [11C]PBR28 uptake following surgery. Results demonstrated that, compared with pre-operative baseline, [11C]PBR28 binding in the brain was globally downregulated at 1 month following major orthopedic surgery, possibly suggesting downregulation of the immune system of the brain. No significant relationship was identified between post-operative delirium and [11C]PBR28 binding, possibly due to a small number (n = 6) of delirium cases in the sample. Additionally, no significant relationships were identified between [11C]PBR28 binding and CSF/plasma biomarkers of inflammation. Collectively, these results contribute to the literature by demonstrating in a sizeable sample the effect of major surgery on neuroimmune activation and preliminary evidence identifying no apparent associations between [11C]PBR28 binding and fluid inflammatory markers or post-operative delirium.

IntroductionWe examined whether educational attainment differentially contributes to cognitive reserve (CR) across race/ethnicity.MethodsA total of 1553 non-Hispanic Whites (Whites), non-Hispanic Blacks (Blacks), and Hispanics in the Washington Heights-Inwood Columbia Aging Project (WHICAP) completed structural magnetic resonance imaging. Mixture growth curve modeling was used to examine whether the effect of brain integrity indicators (hippocampal volume, cortical thickness, and white matter hyperintensity [WMH] volumes) on memory and language trajectories was modified by education across racial/ethnic groups.ResultsHigher educational attainment attenuated the negative impact of WMH burden on memory (β=-0.03; 99% CI: -0.071, -0.002) and language decline (β=-0.024; 99% CI:- 0.044, -0.004), as well as the impact of cortical thinning on level of language performance for Whites, but not for Blacks or Hispanics.DiscussionEducational attainment does not contribute to CR similarly across racial/ethnic groups.

INTRODUCTION: Older adults, including those with mild cognitive impairment (MCI), are increasingly undergoing surgery. METHODS: Relative risks of MCI alone or with delirium on adverse outcomes were estimated in an ongoing prospective, observational cohort study of 560 non-demented adults ≥70 years old. RESULTS: MCI (n=61, 11%) was associated with increased relative risk (RR) of delirium (RR=1.9, p

Objectives: The purpose of this study was to investigate the longitudinal trajectory of self- and informant-subjective cognitive complaints (SCC), and to determine if SCC predict longitudinal changes in objective measures (OM) of cognitive function. Methods: The study included healthy and cognitively normal late middle-aged adults enriched with a family history of AD who were evaluated at up to three visits over a 4-year period. At each visit (Visit 1–3), self- and informant-SCC and OM were evaluated. Linear mixed models were used to determine if the longitudinal rate of change of self- and informant-SCC were associated with demographic variables, depressive symptoms, family history (FH), and apolipoprotein epsilon 4 (APOE4) status. The same modeling approach was used to examine the effect of Visit 1 SCC on longitudinal cognitive change after controlling for the same variables. Results: At Visit 1, more self-SCC were associated with fewer years of education and more depressive symptoms. SCC were also associated with poorer performance on cognitive measures, such that more self-SCC at Visit 1 were associated with poorer performance on memory and executive functioning measures at Visit 1, while more informant-SCC were associated with faster rate of longitudinal decline on a measure of episodic learning and memory. FH and APOE4 status were not associated with SCC. Discussion: Self- and informant-SCC showed an association with OM, albeit over different time frames in our late middle-aged sample. Additional longitudinal follow-up will likely assist in further clarifying these relationships as our sample ages and more pronounced cognitive changes eventually emerge. (JINS, 2017, 23, 617–626)

Objective:To examine the influence of the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism on longitudinal cognitive trajectories in a large, cognitively healthy cohort enriched for Alzheimer disease (AD) risk and to understand whether β-amyloid (Aβ) burden plays a moderating role in this relationship.Methods:One thousand twenty-three adults (baseline age 54.94 ± 6.41 years) enrolled in the Wisconsin Registry for Alzheimer's Prevention underwent BDNF genotyping and cognitive assessment at up to 5 time points (average follow-up 6.92 ± 3.22 years). A subset (n = 140) underwent 11C-Pittsburgh compound B (PiB) scanning. Covariate-adjusted mixed-effects regression models were used to elucidate the effect of BDNF on cognitive trajectories in 4 cognitive domains, including verbal learning and memory, speed and flexibility, working memory, and immediate memory. Secondary mixed-effects regression models were conducted to examine whether Aβ burden, indexed by composite PiB load, modified any observed BDNF-related cognitive trajectories.Results:Compared to BDNF Val/Val homozygotes, Met carriers showed steeper decline in verbal learning and memory (p = 0.002) and speed and flexibility (p = 0.017). In addition, Aβ burden moderated the relationship between BDNF and verbal learning and memory such that Met carriers with greater Aβ burden showed even steeper cognitive decline (p = 0.033).Conclusions:In a middle-aged cohort with AD risk, carriage of the BDNF Met allele was associated with steeper decline in episodic memory and executive function. This decline was exacerbated by greater Aβ burden. These results suggest that the BDNF Val66Met polymorphism may play an important role in cognitive decline and could be considered as a target for novel AD therapeutics.

Positive affect is associated with a number of health benefits; however, few studies have examined the relationship between positive affect and cerebral glucose metabolism, a key energy source for neuronal function and a possible index of brain health. We sought to determine if positive affect was associated with cerebral glucose metabolism in late middle-aged adults (n = 133). Participants completed the positive affect subscale of the Center for Epidemiological Studies Depression Scale at two time points over a two-year period and underwent 18F-fluorodeoxyglucose-positron emission tomography scanning. After controlling for age, sex, perceived health status, depressive symptoms, anti-depressant use, family history of Alzheimer's disease, APOE ε4 status and interval between visits, positive affect was associated with greater cerebral glucose metabolism across para-/limbic, frontal, temporal and parietal regions. Our findings provide evidence that positive affect in late midlife is associated with greater brain health in regions involved in affective processing and also known to be susceptible to early neuropathological processes. The current findings may have implications for interventions aimed at increasing positive affect to attenuate early neuropathological changes in at-risk individuals.

Falls are viewed as a preventable cause of injury, functional loss, and death in older adults with dementia, and have been used as a marker of quality of care in long-term care facilities. Despite intensive intervention around fall prevention in these settings, falls and injury remain frequent, particularly among residents in the advanced stages of dementia. In this clinical review, we consider the common challenges and pitfalls in both the management of falls and the provision of palliative care in advanced dementia. We then describe a palliative approach to falls in advanced dementia that involves identifying individuals who would benefit from this care approach, framing falls and loss of mobility as a quality of life issue, and devising an individualized symptom assessment and management plan. A palliative approach can lead to recognition and acceptance that recurrent falls are often symptomatic of advanced dementia, and that not all falls are preventable. We conclude that falls in the advanced stage of dementia can be sentinel events indicating the need for a palliative approach to care. Rather than replace falls prevention activities, a palliative approach to falls prompts us to select dementia stage-appropriate interventions with a focus on symptom management, comfort, and dignity.

Alzheimer's disease (AD) is characterized by substantial neurodegeneration, including both cortical atrophy and loss of underlying white matter fiber tracts. Understanding longitudinal alterations to white matter may provide new insights into trajectories of brain change in both healthy aging and AD, and fluid biomarkers may be particularly useful in this effort. To examine this, 151 late-middle-aged participants enriched with risk for AD with at least one lumbar puncture and two diffusion tensor imaging (DTI) scans were selected for analysis from two large observational and longitudinally followed cohorts. Cerebrospinal fluid (CSF) was assayed for biomarkers of AD-specific pathology (phosphorylated-tau/Aβ42 ratio), axonal degeneration (neurofilament light chain protein, NFL), dendritic degeneration (neurogranin), and inflammation (chitinase-3-like protein 1, YKL-40). Linear mixed effects models were performed to test the hypothesis that biomarkers for AD, neurodegeneration, and inflammation, or two-year change in those biomarkers, would be associated with worse white matter health overall and/or progressively worsening white matter health over time. At baseline in the cingulum, phosphorylated-tau/Aβ42 was associated with higher mean diffusivity (MD) overall (intercept) and YKL-40 was associated with increases in MD over time. Two-year change in neurogranin was associated with higher mean diffusivity and lower fractional anisotropy overall (intercepts) across white matter in the entire brain and in the cingulum. These findings suggest that biomarkers for AD, neurodegeneration, and inflammation are potentially important indicators of declining white matter health in a cognitively healthy, late-middle-aged cohort.

Educational attainment is associated with cognition among older adults, but this association is complex and not well understood. While associated with better cognition among healthy adults, more education predicts faster decline in older adults with cognitive impairment. Education may influence cognitive functioning through mechanisms involving brain maintenance (BM: reduced age-related pathology) or cognitive reserve (CR: altered pathology-cognition association). We examined evidence for each mechanism by quantifying main and interaction effects of education within a well-studied pathway involving systolic blood pressure, white matter hyperintensities (WMH), and episodic memory in 2 samples without dementia at the baseline (total N = 1136). There were no effects of education on systolic blood pressure or WMH, suggesting a lack of evidence for BM. In the sample less likely to progress to dementia, education attenuated the effect of WMH on memory at the baseline. In the sample more likely to progress to dementia, education exacerbated this effect at the baseline. These moderations provide evidence for a CR mechanism and are consistent with previous findings of faster decline once CR is depleted.

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., Highlights • Derives novel representation of brain connectivity identifying associations between changes in white matter tracts and CSF • Demonstrates statistically significant associations between white matter microstructure and CSF at the asymptomatic stage • Shows that biomarkers of both neurofibrillary tangles and synaptic dysfunction are associated with altered connectivity

Delirium is common among dementia patients and can be distressing to both patients and their caregivers. Distress, the subjective experience of delirium (i.e. “delirium burden”), was measured using newly developed patient and caregiver delirium-burden questionnaires, in a subset of patients and/or caregivers (n=267) from the Better Assessment of Illness (BASIL) study, an ongoing prospective, observational study of surgical and medical patients ≥70 years old. Thirty percent of the cohort had dementia as defined by proxy Informant Questionnaire on Cognitive Decline in the Elderly score ≥3.5 or ICD-9 codes from chart review; 22% experienced delirium by the Confusion Assessment Method (CAM). Delirium-burden instruments were reliable in patients with dementia (Cronbach’s α=0.82) and their caregivers (α=0.77). Delirium resulted in higher caregiver delirium-burden, regardless of dementia status (mean difference [compared to cognitively normal, CN]=6.87, 95% CI [4.02–9.72] with dementia; mean difference=6.03, 95% CI [2.80–9.27] without dementia). Delirium increased patient delirium-burden overall (mean difference [compared to CN]=7.99, 95% CI [5.57–10.42]); this effect was attenuated by dementia (mean difference [compared to CN =2.97, 95% CI [0.34–5.59]). Caregiver delirium-burden correlated with delirium-severity in patients with (r=.21) and without dementia (r=0.30); however, patient delirium-burden correlated with delirium severity only in patients without (r=.43) but not with dementia (r=.06). Instruments for measuring delirium burden are useful for estimating distress in caregivers and in patients without dementia; however, reporting in patients with dementia may be limited. Such measures are important to ultimately lessen the distress of delirium for patients and family caregivers.

Frailty is present in almost half of all older surgical patients. Although frailty has been associated with cognitive decline, this has not been examined in the context of surgery. It is also not known if this relationship is independent of delirium, an established risk factor for postoperative cognitive decline. We probed these questions in the Successful Aging after Elective Surgery cohort of 560 dementia-free older adults (≥70 years old) undergoing elective surgery. Frailty and delirium were measured, respectively, by the Fried Frailty Index and the Confusion Assessment Method supplemented by medical chart review. Postoperative cognitive trajectory was measured as the slope of the General Cognitive Performance (GCP) score, a composite derived from results of a neuropsychological battery administered 2–36 months post-surgery. 64 (12%) of patients were robust, 280 (56%) were pre-frail, and 160 (32%) were frail. Delirium occurred in 134 patients (24%) overall. Compared to the rate of GCP decline among robust patients, decline was steeper by -0.47 points/year (95% CI -0.83, -0.14, p=.005) among pre-frail patients and by -0.48 points/year (95% CI -0.88, -0.07, p=.02) among frail patients. This effect was independent of age, sex, and education. Notably, the known influence of delirium on cognitive decline did not account for the association between frailty and cognitive decline. These results suggest pre-frailty, frailty and delirium are independently associated with accelerated postoperative cognitive decline, with effects of similar magnitude to each other and to mild cognitive impairment. Preoperative frailty screening could identify patients at higher risk of cognitive decline after surgery.

It is not known whether computerized cognitive assessments, like the CogState battery, are sensitive to preclinical cognitive changes or pathology in people at risk for Alzheimer’s disease (AD). In 469 late middle-aged participants from the Wisconsin Registry for Alzheimer’s Prevention (mean age 63.8±7 years at testing; 67% female; 39% APOE4+), we examined relationships between a CogState abbreviated battery (CAB) of seven tests and demographic characteristics, traditional paper-based neuropsychological tests as well as a composite cognitive impairment index, cognitive impairment status (determined by consensus review); and biomarkers for amyloid and tau (CSF phosphorylated-tau/Aβ42 and global PET-PiB burden) and neural injury (CSF neurofilament light protein). CSF and PET-PiB were collected in n=71 and n=91 participants, respectively, approximately four years prior to CAB testing. For comparison, we examined three traditional tests of delayed memory in parallel. Similar to studies in older samples, the CAB was less influenced by demographic factors than traditional tests. CAB tests were generally correlated with most paper-based cognitive tests examined and mapped onto the same cognitive domains. Greater composite cognitive impairment index was associated with worse performance on all CAB tests. Cognitively impaired participants performed significantly worse compared to normal controls on all but one CAB test. Poorer One Card Learning test performance was associated with higher levels of CSF phosphorylated-tau/Aβ42. These results support the use of the CogState battery as measures of early cognitive impairment in studies of people at risk for AD.

IntroductionBiomarkers are urgently needed for the critical yet understudied preclinical stage of Alzheimer's disease (AD).MethodsCerebrospinal fluid (CSF) collection, [C-11]Pittsburgh compound B (PiB) amyloid imaging, and magnetic resonance imaging were acquired in 104 cognitively healthy adults enriched with risk for sporadic AD. Image-derived cerebral β-amyloid (Aβ) burden, measured concurrently and longitudinally, was regressed on CSF measures of Aβ, neural injury, and inflammation, as well as ratios with Aβ42. Linear mixed-effects regression was used to model the effect of the CSF measures that predicted longitudinal brain amyloid accumulation on longitudinal cognitive decline, measured by memory test scores.ResultsAt baseline, Aβ42/Aβ40 and all CSF ratios to Aβ42 were associated with PiB binding in AD-vulnerable regions. Longitudinally, Aβ42/Aβ40 and ratios of total tau (t-tau), phosphorylated-tau (p-tau), neurofilament light protein, and monocyte chemoattractant protein-1 to Aβ42 were associated with increased Aβ deposition over 2 years, predominantly in lateral parietal and temporal cortex. However, these CSF ratios were not significantly associated with cognitive decline, and the effect seems to be largely driven by Aβ42 in the denominator.DiscussionThese results corroborate previous findings that t-tau/Aβ42 and p-tau/Aβ42 are the strongest candidate biomarkers during the preclinical time frame. They support a framework in which neural injury and amyloid deposition are likely occurring simultaneously. It may be that neurodegenerative processes influence progressive amyloid accumulation, even in the preclinical time frame. CSF biomarkers for nonspecific axonal injury and inflammation may provide more information at more advanced stages of the preclinical time course.

IntroductionAlthough cerebrovascular disease has long been known to co-occur with Alzheimer's disease (AD), recent studies suggest an etiologic contribution to AD pathogenesis. We used four dimensional (4D)-flow magnetic resonance imaging (MRI) to evaluate blood flow and pulsatility indices in the circle of Willis. We hypothesized decreased mean blood flow and increased pulsatility, metrics indicative of poor vascular health, would be associated with cerebral atrophy and an AD cerebrospinal fluid (CSF) profile.MethodsA total of 312 patients along the AD continuum (172 middle aged, 60 cognitively healthy older, 44 mild cognitive impairment, and 36 AD) underwent MRI, CSF, and medical examinations. Regression was used to predict CSF biomarkers and atrophy from 4D-flow and analysis of covariance to compare vascular health between groups.ResultsDecreased mean flow in the middle cerebral artery (MCA) and superior portion of the internal carotid artery (sICA) and increased pulsatility in the MCA were associated with greater brain atrophy. Decreased mean flow in the sICA was associated with lower amyloid beta 1–42 (Aβ42) in the CSF, a pathologic biomarker profile associated with AD. Interestingly, although metrics of flow and pulsatility differed markedly across the AD spectrum, there were no significant differences in cardiovascular risk score, mean arterial pressure, and pulse pressure across the three age-matched older cohorts.DiscussionBy measuring intracranial arterial health directly with 4D-flow MRI, these data suggest that intracranial arterial health is compromised in symptomatic AD. Even after accounting for disease stage, cerebral artery health is associated with atrophy and an AD Aβ42 profile, suggesting neurovascular health may contribute to the etiopathogenesis of AD.

Major surgery is associated with a systemic inflammatory cascade that is thought, in some cases, to contribute to transient and/or sustained cognitive decline, possibly through neuroinflammatory mechanisms. However, the relationship between surgery, peripheral and central nervous system inflammation, and post-operative cognitive outcomes remains unclear in humans, primarily owing to limitations of in vivo biomarkers of neuroinflammation which vary in sensitivity, specificity, validity, and reliability. In the present study, [11C]PBR28 positron emission tomography, cerebrospinal fluid (CSF), and blood plasma biomarkers of inflammation were assessed pre-operatively and 1-month post-operatively in a cohort of patients (N = 36; 30 females; ≥70 years old) undergoing major orthopedic surgery under spinal anesthesia. Delirium incidence and severity were evaluated daily during hospitalization. Whole-brain voxel-wise and regions-of-interest analyses were performed to determine the magnitude and spatial extent of changes in [11C]PBR28 uptake following surgery. Results demonstrated that, compared with pre-operative baseline, [11C]PBR28 binding in the brain was globally downregulated at 1 month following major orthopedic surgery, possibly suggesting downregulation of the immune system of the brain. No significant relationship was identified between post-operative delirium and [11C]PBR28 binding, possibly due to a small number (n = 6) of delirium cases in the sample. Additionally, no significant relationships were identified between [11C]PBR28 binding and CSF/plasma biomarkers of inflammation. Collectively, these results contribute to the literature by demonstrating in a sizeable sample the effect of major surgery on neuroimmune activation and preliminary evidence identifying no apparent associations between [11C]PBR28 binding and fluid inflammatory markers or post-operative delirium.

Introduction An Alzheimer's disease (AD) biomarker adjusted for age-related brain changes should improve specificity for AD-related pathological burden. Methods We calculated a brain-age-adjusted “personalized AD cortical thickness index” (pADi) in mild cognitive impairment patients from the Alzheimer's Disease Neuroimaging Initiative. We performed receiver operating characteristic analysis for discrimination between patients with and without cerebrospinal fluid evidence of AD and logistic regression in an independent sample to determine if a dichotomized pADi predicted conversion to AD dementia. Results Receiver operating characteristic area under the curve was 0.69 and 0.72 in the two samples. Three empirical methods identified the same cut-point for pADi in the discovery sample. In the validation sample, 83% of pADi+ mild cognitive impairment patients were cerebrospinal fluid AD biomarker positive. pADi+ mild cognitive impairment patients (n = 63, 38%) were more likely to progress to AD dementia after 1 (odds ratio = 2.9) and 3 (odds ratio = 2.6) years. Discussion The pADi is a personalized, magnetic resonance imaging–derived AD biomarker that predicts progression to dementia., Highlights • The personalized AD cortical thickness index (pADi) is a personalized magnetic resonance imaging–derived, brain-age-adjusted Alzheimer's disease (AD) biomarker. • The pADi accurately identifies mild cognitive impairment patients with cerebrospinal fluid markers of AD. • The pADi was consistent across two independent samples with 1.5T and 3T magnetic resonance imaging data. • An optimal cut-point predicted progression to AD dementia over 1 or 3 years. • The pADi can identify mild cognitive impairment likely due to AD in individual patients.

BACKGROUND AND OBJECTIVES: Delirium creates distinct emotional distress in patients and family caregivers, yet there are limited tools to assess the experience. Our objective was to develop separate patient and family caregiver delirium burden instruments and to test their content and construct validity. RESEARCH DESIGN AND METHODS: Two hundred forty-seven patients and 213 family caregivers were selected from an ongoing prospective cohort of medical-surgical admissions aged ≥70 years old. New patient and family caregiver delirium burden instruments were developed and used to measure the subjective experiences of in-hospital delirium. Delirium and delirium severity were measured by the Confusion Assessment Method (CAM) and CAM-Severity (long form). RESULTS: Both Delirium Burden (DEL-B) instruments consist of eight questions and are measured on a 0 – 40 point scale. Final questions had good clarity and relevancy, as rated by the expert panel, and good internal consistency (Cronbach’s α = .82–.86). In the cohort validation, Patient DEL-B (DEL-B-P) was 5.1 points higher and Family Caregiver DEL-B (DEL-B-C) was 5.8 points higher, on average, for patients who developed delirium compared to those who did not (p < .001). Test–retest reliability of DEL-B-C at baseline and 1 month was strong (correlation = .73). Delirium severity was mildly-moderately correlated with DEL-B-P (correlation = .34) and DEL-B-C (correlation = .26), suggesting contribution of other factors. DISCUSSION AND IMPLICATIONS: We created instruments to reliably measure and evaluate the burden of delirium for patients and their family caregivers. Although additional validation is indicated, these instruments provide a key first step toward measuring and improving the subjective experience of delirium for patients and their families.

Prevention of postoperative delirium and long-term cognitive decline (LTCD) requires risk quantification that is valid in the general clinical setting. Existing prediction rules were primarily developed using stepwise regression, which tends to be overly influenced by specific data sets. We explored multiple different machine learning (ML) algorithms to predict delirium and LTCD (2–36 months). ML better protects against overfitting. We used model development and validation samples from the SAGES cohort (N = 560 adults ≥70 years). A cross-validated logistic regression approach generated the optimal predictive model for delirium (sensitivity 73%), while a random forest optimally prediction of magnitude of LTCD (R2 .20). Pre-operative cognitive level and comorbidity were important in predicting both outcomes, but the final models were otherwise distinct. These results demonstrate the utility of ML for generalizable prediction in this setting and underscores the contribution of baseline vulnerability to risk of delirium and cognitive decline.

Midlife may be an ideal window for intervention in Alzheimer's disease (AD). To determine whether sleep is associated with early signs of AD neuropathology (amyloid deposition) in late midlife, we imaged brain amyloid deposits using positron emission tomography with [C-11]Pittsburgh Compound B (PiB), and assessed sleep with the Epworth Sleepiness Scale and the Medical Outcomes Study Sleep Scale in 98 cognitively healthy adults (aged 62.4 ± 5.7 years) from the Wisconsin Registry for Alzheimer's Prevention. We used multiple regressions to test the extent to which sleep scores predicted regional amyloid burden. Participants reporting less adequate sleep, more sleep problems, and greater somnolence on the Medical Outcomes Study had greater amyloid burden in AD-sensitive brain regions (angular gyrus, frontal medial orbital cortex, cingulate gyrus, and precuneus). Amyloid was not associated with reported sleep amount, symptoms of sleep-disordered breathing, trouble falling asleep, or Epworth Sleepiness Scale. Poor sleep may be a risk factor for AD and a potential early marker of AD or target for preventative interventions in midlife.

It is becoming increasingly recognized that cerebrovascular disease is a contributing factor in the pathogenesis of Alzheimer’s disease (AD). A unique 4D-Flow magnetic resonance imaging (MRI) technique, phase contrast vastly undersampled isotropic projection imaging, (PC VIPR), enables examination of angiographic and quantitative metrics of blood flow in the arteries of the Circle of Willis within a single MRI acquisition. Thirty-eight participants with Mild Cognitive Impairment (MCI) underwent a comprehensive neuroimaging protocol (including 4D-Flow imaging) and a standard neuropsychological battery. A subset of participants (N=22) also underwent lumbar puncture and had cerebrospinal fluid (CSF) assayed for AD biomarkers. Cut-offs for biomarker positivity in CSF resulting from a Receiver Operating Characteristic (ROC) curve analysis of AD cases and controls from the larger Wisconsin Alzheimer’s Disease Research Center cohort were used to classify MCI participants as biomarker positive or negative on amyloid-β (Aβ42), total-tau and total-tau/Aβ42 ratio. Internal carotid artery (ICA) and middle cerebral artery (MCA) mean flow were associated with executive functioning performance, with lower mean flow corresponding to worse performance. MCI participants who were biomarker positive for Aβ42 had lower ICA mean flow than did those who were Aβ42 negative. In sum, mean ICA and MCA arterial flow was associated with cognitive performance in participants with MCI and lower flow in the ICA was associated with amyloid positivity. This provides further evidence for vascular health as a contributing factor in the etiopathogenesis of AD, and could represent a point to intervene in the disease process.

Patients with dementia due to Alzheimer's disease (AD) have increased risk of developing delirium. This study investigated the relationship between a magnetic resonance imaging (MRI)–derived biomarker associated with preclinical AD and postoperative delirium. Participants were older adults (≥70 years) without dementia who underwent preoperative MRI and elective surgery. Delirium incidence and severity were evaluated daily during hospitalization. Cortical thickness was averaged across a published set of a priori brain regions to derive a measure known as the “AD signature.” Logistic and linear regression was used, respectively, to test whether the AD signature was associated with delirium incidence in the entire sample (N = 145) or with the severity of delirium among those who developed delirium (N = 32). Thinner cortex in the AD signature did not predict incidence of delirium (odds ratio = 1.15, p = 0.38) but was associated with greater delirium severity among those who developed delirium (b = −1.2, p = 0.014). These results suggest that thinner cortices, perhaps reflecting underlying neurodegeneration due to preclinical AD, may serve as a vulnerability factor that increases severity once delirium occurs.

Polygenic risk scores (PRSs) have been used to combine the effects of variants with small effects identified by genome-wide association studies. We explore the potential for using pathway-specific PRSs as predictors of early changes in Alzheimer’s disease (AD)-related biomarkers and cognitive function. Participants were from the Wisconsin Registry for Alzheimer’s Prevention, a longitudinal study of adults who were cognitively asymptomatic at enrollment and enriched for a parental history of AD. Using genes associated with AD in the International Genomics of Alzheimer’s Project’s meta-analysis, we identified clusters of genes that grouped into pathways involved in β-amyloid (Aβ) deposition and neurodegeneration: Aβ clearance, cholesterol metabolism, and immune response. Weighted pathway-specific and overall PRSs were developed and compared to APOE alone. Mixed models were used to assess whether each PRS was associated with cognition in 1,200 individuals, cerebral Aβ deposition measured using amyloid ligand (Pittsburgh compound B) positron emission imaging (PET) in 168 individuals, and cerebrospinal fluid (CSF) Aβ deposition, neurodegeneration, and tau pathology in 111 individuals, with replication performed in an independent sample. We found that PRSs including APOE appeared to be driven by the inclusion of APOE, suggesting that the pathway-specific PRSs used here were not more predictive than an overall PRS or APOE alone. However, pathway-specific PRSs could prove to be useful as more knowledge is gained on the genetic variants involved in specific biological pathways of AD.

To determine the relationship between amyloid burden and neural function in healthy adults at risk for Alzheimer's Disease (AD), we used multimodal imaging with [C-11]Pittsburgh compound B positron emission tomography, [F-18]fluorodeoxyglucose, positron emission tomography , and magnetic resonance imaging, together with cognitive measurement in 201 subjects (mean age, 60.1 years; range, 46-73 years) from the Wisconsin Registry for Alzheimer's Prevention. Using a qualitative rating, 18% of the samples were strongly positive Beta-amyloid (Aβ+), 41% indeterminate (Aβi), and 41% negative (Aβ-). Aβ+ was associated with older age, female sex, and showed trends for maternal family history of AD and APOE4. Relative to the Aβ- group, Aβ+ and Aβi participants had increased glucose metabolism in the bilateral thalamus; Aβ+ participants also had increased metabolism in the bilateral superior temporal gyrus. Aβ+ participants exhibited increased gray matter in the lateral parietal lobe bilaterally relative to the Aβ- group, and no areas of significant atrophy. Cognitive performance and self report cognitive and affective symptoms did not differ between groups. Amyloid burden can be identified in adults at a mean age of 60 years and is accompanied by glucometabolic increases in specific areas, but not atrophy or cognitive loss. This asymptomatic stage may be an opportune window for intervention to prevent progression to symptomatic AD.

Some cognitively healthy individuals develop brain amyloid accumulation, suggestive of incipient Alzheimer's disease (AD), but the effect of amyloid on other potentially informative imaging modalities, such as Diffusion Tensor Imaging (DTI), in characterizing brain changes in preclinical AD requires further exploration. In this study, a sample (N = 139, mean age 60.6, range 46 to 71) from the Wisconsin Registry for Alzheimer's Prevention (WRAP), a cohort enriched for AD risk factors, was recruited for a multimodal imaging investigation that included DTI and [C-11]Pittsburgh Compound B (PiB) positron emission tomography (PET). Participants were grouped as amyloid positive (Aβ+), amyloid indeterminate (Aβi), or amyloid negative (Aβ−) based on the amount and pattern of amyloid deposition. Regional voxel-wise analyses of four DTI metrics, fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da), and radial diffusivity (Dr), were performed based on amyloid grouping. Three regions of interest (ROIs), the cingulum adjacent to the corpus callosum, hippocampal cingulum, and lateral fornix, were selected based on their involvement in the early stages of AD. Voxel-wise analysis revealed higher FA among Aβ+ compared to Aβ− in all three ROIs and in Aβi compared to Aβ− in the cingulum adjacent to the corpus callosum. Follow-up exploratory whole-brain analyses were consistent with the ROI findings, revealing multiple regions where higher FA was associated with greater amyloid. Lower fronto-lateral gray matter MD was associated with higher amyloid burden. Further investigation showed a negative correlation between MD and PiB signal, suggesting that Aβ accumulation impairs diffusion. Interestingly, these findings in a largely presymptomatic sample are in contradistinction to relationships reported in the literature in symptomatic disease stages of Mild Cognitive Impairment and AD, which usually show higher MD and lower FA. Together with analyses showing that cognitive function in these participants is not associated with any of the four DTI metrics, the present results suggest an early relationship between PiB and DTI, which may be a meaningful indicator of the initiating or compensatory mechanisms of AD prior to cognitive decline., Graphical abstract, Highlights • Study cohort of preclinical subjects (N = 139) at risk for Alzheimer's disease • Examination of four DTI metrics in three groups based on global amyloid load • Greater amyloid load was associated with higher fractional anisotropy. • Diffusivity was negatively associated with amyloid in fronto-lateral gray matter. • DTI metrics were not correlated with cognition at this early disease stage.

Few studies have investigated the relationship between frailty and postoperative delirium. We used the Confusion Assessment Method (CAM) supplemented by medical chart review, CAM-Severity (CAM-S) peak score, and Fried Frailty Index, respectively, to measure delirium, delirium severity, and frailty in the SAGES cohort of 560 older adults (≥70 years) undergoing elective surgery. Delirium prevalence was 13% (8/64), 21% (58/280), and 27% (43/160) in robust, pre-frail, and frail patients, respectively. Frail (odds ratio=2.6, 95% CI 1.1–5.8) but not pre-frail (odds ratio=1.8, 95% CI 0.8–4.1) patients had greater odds of developing delirium compared to robust patients. Frailty was also associated with greater delirium severity: CAM-S peak scores were 0.6 points (95% CI 0.3–0.9) higher in pre-frail patients and 1.7 points (95% CI 1.4–2.0) higher in frail patients compared to robust patients, on average. Preoperative screening for frailty could identify patients who are more likely to develop delirium and have more severe delirium.