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The reference standard for amyloid-PET quantification requires structural MRI (sMRI) for preprocessing in both multi-site research studies and clinical trials. Here we describe rPOP (robust PET-Only Processing), a MATLAB-based MRI-free pipeline implementing non-linear warping and differential smoothing of amyloid-PET scans performed with any of the FDA-approved radiotracers (18F-florbetapir/FBP, 18F-florbetaben/FBB or 18F-flutemetamol/FLUTE). Each image undergoes spatial normalization based on weighted PET templates and data-driven differential smoothing, then allowing users to perform their quantification of choice. Prior to normalization, users can choose whether to automatically reset the origin of the image to the center of mass or proceed with the pipeline with the image as it is. We validate rPOP with n = 740 (514 FBP, 182 FBB, 44 FLUTE) amyloid-PET scans from the Imaging Dementia—Evidence for Amyloid Scanning – Brain Health Registry sub-study (IDEAS-BHR) and n = 1,518 scans from the Alzheimer's Disease Neuroimaging Initiative (n = 1,249 FBP, n = 269 FBB), including heterogeneous acquisition and reconstruction protocols. After running rPOP, a standard quantification to extract Standardized Uptake Value ratios and the respective Centiloids conversion was performed. rPOP-based amyloid status (using an independent pathology-based threshold of ≥24.4 Centiloid units) was compared with either local visual reads (IDEAS-BHR, n = 663 with complete valid data and reads available) or with amyloid status derived from an MRI-based PET processing pipeline (ADNI, thresholds of >20/>18 Centiloids for FBP/FBB). Finally, within the ADNI dataset, we tested the linear associations between rPOP- and MRI-based Centiloid values. rPOP achieved accurate warping for N = 2,233/2,258 (98.9%) in the first pass. Of the N = 25 warping failures, 24 were rescued with manual reorientation and origin reset prior to warping. We observed high concordance between rPOP-based amyloid status and both visual reads (IDEAS-BHR, Cohen's k = 0.72 [0.7–0.74], ∼86% concordance) or MRI-pipeline based amyloid status (ADNI, k = 0.88 [0.87–0.89], ∼94% concordance). rPOP- and MRI-pipeline based Centiloids were strongly linearly related (R2:0.95, p<0.001), with this association being significantly modulated by estimated PET resolution (β= -0.016, p<0.001). rPOP provides reliable MRI-free amyloid-PET warping and quantification, leveraging widely available software and only requiring an attenuation-corrected amyloid-PET image as input. The rPOP pipeline enables the comparison and merging of heterogeneous datasets and is publicly available at https://github.com/leoiacca/rPOP.

Aims: To investigate midlife cholesterol in relation to Alzheimer’s disease (AD) and vascular dementia (VaD) in a large multiethnic cohort of women and men. Methods: The Kaiser Permanente Northern California Medical Group (healthcare delivery organization) formed the database for this study. The 9,844 participants underwent detailed health evaluations during 1964–1973 at ages 40–45 years; they were still members of the health plan in 1994. AD and VaD were ascertained by medical records between 1 January 1994 and 1 June 2007. Cox proportional hazards models – adjusted for age, education, race/ethnic group, sex, midlife diabetes, hypertension, BMI and late-life stroke – were conducted. Results: In total, 469 participants had AD and 127 had VaD. With desirable cholesterol levels (<200 mg/dl) as a reference, hazard ratios (HR) and 95% CI for AD were 1.23 (0.97–1.55) and 1.57 (1.23–2.01) for borderline (200–239 mg/dl) and high cholesterol (≥240 mg/dl), respectively. HR and 95% CI for VaD were 1.50 (1.01–2.23) for borderline and 1.26 (0.82–1.96) for high cholesterol. Further analyses for AD (cholesterol quartiles, 1st quartile reference) indicated that cholesterol levels >220 mg/dl were a significant risk factor: HR were 1.31 (1.01–1.71; 3rd quartile, 221–248 mg/dl) and 1.58 (1.22–2.06; 4th quartile, 249–500 mg/dl). Conclusion: Midlife serum total cholesterol was associated with an increased risk of AD and VaD. Even moderately elevated cholesterol increased dementia risk. Dementia risk factors need to be addressed as early as midlife, before underlying disease(s) or symptoms appear.

ObjectivesTo evaluate how insurance influences the risk of a dementia diagnosis among a large, diverse cohort of US civilian adults with traumatic brain injury (TBI) over a 22-year period.DesignThis is a retrospective cohort study involving individuals diagnosed with TBI.SettingThe study used the Merative MarketScan Research Database, specifically drawing from the Commercial Claims and Encounters, Medicare Supplemental and Medicaid databases, from 2000 to 2022 in the USA. These databases provide comprehensive insights into healthcare services received by enrollees, including inpatient and outpatient services, outpatient prescription claims, clinical utilisation records and healthcare expenditures.Participants267 473 adults aged 55 and older who were diagnosed with a TBI between 1 January 2000 and 31 December 2022. Individuals with unknown TBI severity and dementia claims 2 years preceding TBI were excluded. TBI and dementia diagnoses were identified using International Classification of Disease 9th and 10th editions codes from inpatient and outpatient admission records.InterventionsNone.Primary and secondary outcome measuresWe compared the incidence of all-cause dementia across different insurance types to assess potential disparities in diagnosis following TBI. Cox proportional hazards models, with age as the time scale, were used to study the association between insurance type and dementia diagnosis following a TBI. Models were adjusted for key demographic variables, medical comorbidities and psychiatric conditions to account for potential confounding.ResultsOf the 267 473 individuals with TBI, 12.7% were diagnosed with dementia over a mean follow-up period of 40 months (SD of 42 months). Dementia incidence differed significantly by insurance type, with 18.2% for Medicaid recipients, 17.3% for Medicare beneficiaries and only 2.3% among individuals with commercial insurance. The adjusted HR for dementia was notably higher among individuals enrolled on Medicaid (HR 2.9, 95% CI: 2.8 to 3.1) and Medicare (HR 2.1, 95% CI: 2.0 to 2.2), when compared with those with commercial insurance.ConclusionsIndividuals with TBI covered by Medicaid and Medicare are significantly more likely to be diagnosed with dementia, with a 2.9-fold and 2.1-fold increase risk, respectively, compared with those with commercial insurance. Addressing insurance-related disparities in dementia diagnosis is crucial for building a more equitable healthcare system. It is essential that individuals with TBI cases, regardless of their insurance type, have access to comprehensive care and preventive interventions to achieve the best possible long-term outcomes.

Cognitive dysfunction, including mild cognitive impairment and dementia, is increasingly recognised as an important comorbidity and complication of diabetes that affects an individual’s well-being and diabetes management, and is associated with diabetes treatment-related complications. Recent guidelines therefore recommend screening for cognitive impairment in older individuals with diabetes. In addition, these guidelines suggest that glucose-lowering treatment should be tailored in those diagnosed with cognitive impairment, to reduce the risk of hypoglycaemia and improve treatment adherence. This review gives an overview of cognitive dysfunction in people with diabetes, briefly describing the clinical features of different stages of cognitive dysfunction and their epidemiology. In particular, it addresses essential additional steps that need to be taken to fully implement the emerging guidelines on screening and management of cognitive dysfunction in diabetes into daily practice.

ObjectivesEvidence on adverse childhood experiences (ACEs) and late-life cognitive outcomes is inconsistent, with little research among diverse racial/ethnic groups. We investigated whether ACE exposures were associated with worse late-life cognition for all racial/ethnic groups and at different ages of exposure.DesignCovariate-adjusted mixed-effects linear regression models estimated associations of: (1) total number of ACEs experienced, (2) earliest age when ACE occurred and (3) type of ACE with overall cognition.SettingKaiser Permanente Northern California members aged 65 years and older, living in Northern California.ParticipantsKaiser Healthy Aging and Diverse Life Experiences study baseline participants, aged 65 years and older (n=1661; including 403 Asian-American, 338 Latino, 427 Black and 493 white participants).ResultsMost respondents (69%) reported one or more ACE, most frequently family illness (36%), domestic violence (23%) and parental divorce (22%). ACE count was not adversely associated with cognition overall (β=0.01; 95% CI −0.01 to 0.03), in any racial/ethnic group or for any age category of exposure. Pooling across all race/ethnicities, parent’s remarriage (β=−0.11; 95% CI −0.20 to −0.03), mother’s death (β=−0.18; 95% CI −0.30 to −0.07) and father’s death (β=−0.11; 95% CI −0.20 to −0.01) were associated with worse cognition.ConclusionAdverse childhood exposures overall were not associated with worse cognition in older adults in a diverse sample, although three ACEs were associated with worse cognitive outcomes.

Background Low socioeconomic status (SES) in early and late life has been associated with lower late-life cognition. Less is known about how changes in SES from childhood to late life are associated with late-life cognition, especially among diverse populations of older adults. Methods In a multi-ethnic sample ( n  = 1353) of older adults, we used linear regression to test associations of change in comprehensive measures of SES (financial, cultural, and social domains) from childhood to late life with semantic memory, episodic memory, and executive function. We tested whether the association between SES trajectory and late-life cognition differed by populations who resided in the U.S. during childhood or immigrated to the U.S. as adults. Results Participants with low childhood/high late-life financial capital had better semantic memory (β = 0.18; 95% CI: 0.04, 0.32) versus those with low financial capital in both childhood and late life, regardless of childhood residence. We observed a significant interaction in the association of verbal episodic memory and cultural capital by childhood residence ( p  = 0.08). Participants with a foreign childhood residence had higher verbal episodic memory if they had low childhood/high late-life cultural capital (β = 0.32; 95% CI: 0.01, 0.63), but lower verbal episodic memory if they had high childhood/low late-life cultural capital (β = − 0.40; 95% CI: − 0.94, 0.13). Having high lifecourse social capital was associated with better verbal episodic memory scores among those with a U.S. childhood (β = 0.34; 95% CI: 0.14, 0.55), but lower verbal episodic memory among those with a foreign childhood (β = − 0.10; 95% CI: − 0.51, 0.31). Conclusions High financial and cultural capital in late life is associated with better cognition, regardless of early childhood SES or childhood residence.

ObjectivesAdverse childhood experiences (ACEs) are associated with higher risk of chronic disease, but little is known about the association with late life cognitive decline. We examined the longitudinal association between ACEs and late-life cognitive decline in the Study of Healthy Aging in African Americans (STAR).DesignLinear mixed models with random intercepts and slope examined the association of individual and composite ACEs with cognitive change adjusting for years from baseline (timescale), baseline age, sex, parental education, childhood socioeconomic status and childhood social support. Participants reported whether they had experienced nine types of ACEs. Executive function and verbal episodic memory were measured up to three times over a 3-year period using the Spanish and English Neuropsychological Assessment Scales.SettingsKaiser Permanente Northern California members living in the Bay Area.ParticipantsSTAR is a cohort study of cognitive ageing launched in 2018 that has enrolled 764 black Americans ages ≥50 years (mean age=67.5; SD=8.5).ResultsTwenty-one per cent of participants reported no ACEs, 24% one ACE, 20% two ACEs, 17% three ACEs and 17% four or more ACEs. Compared with no ACEs, two ACEs (β=0.117; 95% CI 0.052 to 0.182), three ACEs (β=0.075; 95% CI 0.007 to 0.143) and four or more ACEs (β=0.089; 95% CI 0.002 to 0.158) were associated with less decline in executive function. There were no significant associations between number of ACEs and baseline or longitudinal verbal episodic memory or between individual ACEs and executive function or verbal episodic memory.ConclusionIn this cohort of older black Americans, there was no association between ACEs and baseline cognition or cognitive change in verbal episodic memory; however, experiencing ≥ 2 ACEs was associated with less decline in executive function. These results may indicate that participants who survived to age 50+ and experienced ACEs may have cognitive resilience that warrants further investigation.

Background Cardiometabolic diseases (CMDs) including type 2 diabetes, heart disease, and stroke have been linked to a higher risk of dementia. We examined whether high levels of cognitive reserve (CR) can attenuate the increased dementia risk and brain pathologies associated with CMDs. Methods Within the UK Biobank, 216,178 dementia-free participants aged ≥ 60 were followed for up to 15 years. Baseline CMDs and incident dementia were ascertained from medical records, medication use, and medical history. Latent class analysis was used to generate an indicator of CR (low, moderate, and high) based on education, occupational attainment, confiding in others, social contact, leisure activities, and television watching time. A subsample ( n  = 13,663) underwent brain MRI scans during follow-up. Volumes of total gray matter (GMV), hippocampus (HV), and white matter hyperintensities (WMHV) were ascertained, as well as mean diffusivity (MD) and fractional anisotropy (FA) in white matter tracts. Results At baseline, 43,402 (20.1%) participants had at least one CMD. Over a mean follow-up of 11.7 years, 6,600 (3.1%) developed dementia. The presence of CMDs was associated with 57% increased risk of dementia (HR 1.57 [95% CI 1.48, 1.67]). In joint effect analysis, the HRs of dementia for people with CMDs and moderate-to-high CR and low CR were 1.78 [1.66, 1.91] and 2.13 [1.97, 2.30]), respectively (reference: CMD-free, moderate-to-high CR). Dementia risk was 17% lower (HR 0.83 [0.77, 0.91], p  < 0.001) among people with CMDs and moderate-to-high compared to low CR. On brain MRI, CMDs were associated with smaller GMV (β -0.18 [-0.22, -0.13]) and HV (β -0.13 [-0.18, -0.08]) as well as significantly larger WMHV (β 0.06 [0.02, 0.11]) and MD (β 0.08 [0.02, 0.13]). People with CMDs and moderate-to-high compared to low CR had significantly larger GMV and HV, but no differences in WMHV, MD, or FA. Conclusions Among people with CMDs, having a higher level of CR was associated with lower dementia risk and larger gray matter and hippocampal volumes. The results highlight a mentally and socially active life as a modifiable factor that may support cognitive and brain health among people with CMDs.

Background We aimed to develop risk tools for dementia, stroke, myocardial infarction (MI), and diabetes, for adults aged ≥ 65 years using shared risk factors. Methods Data were obtained from 10 population-based cohorts ( N  = 41,755) with median follow-up time (years) for dementia, stroke, MI, and diabetes of 6.2, 7.0, 6.8, and 7.4, respectively. Disease-free participants at baseline were included, and 22 risk factors (sociodemographic, medical, lifestyle, laboratory biomarkers) were evaluated. Two risk tools (DemNCD and DemNCD-LR based on Fine and Gray sub-distribution and logistic regression [LR], respectively) were developed and validated. Predictive accuracies of these risk tools were assessed using Harrel’s C-statistics and area under the curve (AUC) and 95% confidence interval (CI). Model calibration was conducted using Hosmer–Lemeshow goodness of fit test along calibration plots. Results Both the DemNCD and DemNCD-LR resulted in similar predictive accuracy for each outcome. The overall AUC (95% CI) for dementia, stroke, MI, and diabetes risk tool were 0·68 (0·65, 0·70), 0·58 (0·54, 0·61), 0·65 (0·61, 0·68), and 0·68 (0·64, 0·72), respectively, for males. For females, these figures were 0·65 (0·63, 0·67), 0·55 (0·52, 0·57), 0·65 (0·62, 0·68), and 0·61 (0·57, 0·65). Conclusions The DemNCD is the first tool to predict both dementia and multiple cardio-metabolic diseases using comprehensive risk factors and provided similar predictive accuracy to existing risk tools. It has similar predictive accuracy as tools designed for single outcomes in this age-group. DemNCD has the potential to be used in community and clinical settings as it includes self-reported and routinely available clinical measures.

Current efforts to reduce dementia focus on prevention and risk reduction by targeting modifiable risk factors. As dementia and cardiometabolic non-communicable diseases (NCDs) share risk factors, a single risk-estimating tool for dementia and multiple NCDs could be cost-effective and facilitate concurrent assessments as compared with a conventional single approach. The aim of this study is to develop and validate a new risk tool that estimates an individual's risk of developing dementia and other NCDs including diabetes mellitus, stroke and myocardial infarction. Once validated, it could be used by the public and general practitioners. Ten high-quality cohort studies from multiple countries were identified, which met eligibility criteria, including large representative samples, long-term follow-up, data on clinical diagnoses of dementia and NCDs, recognised modifiable risk factors for the four NCDs and mortality data. Pooled harmonised data from the cohorts will be used, with 65% randomly allocated for development of the predictive model and 35% for testing. Predictors include sociodemographic characteristics, general health risk factors and lifestyle/behavioural risk factors. A subdistribution hazard model will assess the risk factors' contribution to the outcome, adjusting for competing mortality risks. Point-based scoring algorithms will be built using predictor weights, internally validated and the discriminative ability and calibration of the model will be assessed for the outcomes. Sensitivity analyses will include recalculating risk scores using logistic regression. Ethics approval is provided by the University of New South Wales Human Research Ethics Committee (UNSW HREC; protocol numbers HC200515, HC3413). All data are deidentified and securely stored on servers at Neuroscience Research Australia. Study findings will be presented at conferences and published in peer-reviewed journals. The tool will be accessible as a public health resource. Knowledge translation and implementation work will explore strategies to apply the tool in clinical practice.