Olfactory testing does not predict β-amyloid, MRI measures of neurodegeneration or vascular pathology in the British 1946 birth cohort.

OBJECTIVE: To explore the value of olfactory identification deficits as a predictor of cerebral β-amyloid status and other markers of brain health in cognitively normal adults aged ~ 70 years. METHODS: Cross-sectional observational cohort study. 389 largely healthy and cognitively normal older adults were recruited from the MRC National Survey of Health and Development (1946 British Birth cohort) and investigated for olfactory identification deficits, as measured by the University of Pennsylvania Smell Identification Test. Outcome measures were imaging markers of brain health derived from 3 T MRI scanning (cortical thickness, entorhinal cortex thickness, white matter hyperintensity volumes); 18F florbetapir amyloid-PET scanning; and cognitive testing results. Participants were assessed at a single centre between March 2015 and January 2018. RESULTS: Mean (± SD) age was 70.6 (± 0.7) years, 50.8% were female. 64.5% had hyposmia and 2.6% anosmia. Olfaction showed no association with β-amyloid status, hippocampal volume, entorhinal cortex thickness, AD signature cortical thickness, white matter hyperintensity volume, or cognition. CONCLUSION AND RELEVANCE: In the early 70s, olfactory function is not a reliable predictor of a range of imaging and cognitive measures of preclinical AD. Olfactory identification deficits are not likely to be a useful means of identifying asymptomatic amyloidosis. Further studies are required to assess if change in olfaction may be a proximity marker for the development of cognitive impairment

Amyloid ? influences the relationship between cortical thickness and vascular load.

INTRODUCTION: Cortical thickness has been proposed as a biomarker of Alzheimer's disease (AD)- related neurodegeneration, but the nature of its relationship with amyloid beta (A?) deposition and white matter hyperintensity volume (WMHV) in cognitively normal adults is unclear. METHODS: We investigated the influences of A? status (negative/positive) and WMHV on cortical thickness in 408 cognitively normal adults aged 69.2 to 71.9 years who underwent 18F-Florbetapir positron emission tomography (PET) and structural magnetic resonance imaging (MRI). Two previously defined Alzheimer's disease (AD) cortical signature regions and the major cortical lobes were selected as regions of interest (ROIs) for cortical thickness. RESULTS: Higher WMHV, but not A? status, predicted lower cortical thickness across all participants, in all ROIs. Conversely, when A?-positive participants were considered alone, higher WMHV predicted higher cortical thickness in a temporal AD-signature region. DISCUSSION: WMHV may differentially influence cortical thickness depending on the presence or absence of A?, potentially reflecting different pathological mechanisms

Neuroimaging, clinical and life course correlates of normal-appearing white matter integrity in 70-year-olds

We investigate associations between normal-appearing white matter (NAWM) microstructural integrity in cognitively normal ∼70-year-olds and concurrently measured brain health and cognition, demographics, genetics and life course cardiovascular health. Participants born in the same week in March 1946 (British 1946 Birth cohort) underwent PET-MRI around age 70. Mean standardized NAWM integrity metrics (fractional anisotropy (FA), mean diffusivity (MD), neurite density index (NDI) and orientation dispersion index (ODI)) were derived from diffusion MRI. Linear regression was used to test associations between NAWM metrics and (1) concurrent measures, including whole brain volume, white matter hyperintensity volume (WMHV), PET amyloid and cognition; (2) the influence of demographic and genetic predictors, including sex, childhood cognition, education, socioeconomic position, and genetic risk for Alzheimer’s Disease (APOE-ε4); (3) systolic and diastolic blood pressure and cardiovascular health (FHS-CVS) across adulthood. Sex interactions were tested. Statistical significance included false discovery rate correction (5%). 362 participants met inclusion criteria (mean age 70 years, 49% female). Higher WMHV was associated with lower FA (b=-0.09 [95%CI:-0.11, -0.06] p<0.01), NDI (b=-0.17 [-0.22, -0.12] p<0.01), and higher MD (b=0.14 [-0.10, -0.17] p<0.01); amyloid (in men) was associated with lower FA (b=-0.04 [-0.08, -0.01] p=0.03) and higher MD (b=0.06 [0.01,0.11] p=0.02). FHS-CVS in later-life (age 69) was associated with NAWM [lower FA (b=-0.06 [-0.09, -0.02] p<0.01), NDI (b=-0.10 [-0.17, -0.03] p<0.01), and higher MD (b=0.09 [0.04,0.14] p<0.01). Significant sex interactions (p<0.05) emerged for midlife cardiovascular health (age 53) and NAWM at 70: marginal effect plots demonstrated, in women only, NAWM was associated with higher midlife FHS-CVS (lower FA and NDI), midlife systolic (lower FA, NDI, and higher MD), and diastolic (lower FA and NDI) blood pressure, and greater blood pressure change between 43 and 53 years (lower FA and NDI), independently of WMHV. In summary, poorer NAWM microstructural integrity in ∼70-year-olds was associated with measures of cerebral small vessel disease, amyloid (in males) and later-life cardiovascular health, demonstrating how NAWM can provide additional information to overt white matter disease. Our findings further show that greater midlife cardiovascular risk and higher blood pressure were associated with poorer NAWM microstructural integrity in females only, suggesting that women’s brains may be more susceptible to the effects of midlife blood pressure and cardiovascular health

Associations of β-Amyloid and Vascular Burden With Rates of Neurodegeneration in Cognitively Normal Members of the 1946 British Birth Cohort

OBJECTIVE: To quantify the independent and interactive associations of amyloid-β (Aβ) and white matter hyperintensity volume (WMHV) - a marker of presumed cerebrovascular disease (CVD) - with rates of neurodegeneration, and to examine the contributions of APOE ε4 and vascular risk measured at different stages of adulthood in cognitively normal members of the 1946 British birth cohort. METHODS: Participants underwent brain MRI and florbetapir-Aβ positron emission tomography as part of Insight 46, an observational population-based study. Changes in whole brain, ventricular and hippocampal volume were directly measured from baseline and repeat volumetric T1 MRI using the Boundary Shift Integral. Linear regression was used to test associations with: baseline Aβ deposition; baseline WMHV; APOE ε4; and office-based Framingham heart study-cardiovascular risk scores (FHS-CVS) and systolic blood pressure (BP) at ages 36, 53 and 69 years. RESULTS: 346 cognitively normal participants (mean [SD] age at baseline scan 70.5 [0.6] years; 48% female) had high-quality T1 MRI data from both time-points (mean [SD] scan interval 2.4 [0.2] years). Being Aβ positive at baseline was associated with 0.87 ml/year faster whole brain atrophy (95% CI 0.03, 1.72), 0.39 ml/year greater ventricular expansion (95% CI 0.16, 0.64) and 0.016 ml/year faster hippocampal atrophy (95% CI 0.004, 0.027), while each 10 ml additional WMHV at baseline was associated with 1.07 ml/year faster whole brain atrophy (95% CI 0.47, 1.67), 0.31 ml/year greater ventricular expansion (95% CI 0.13, 0.60) and 0.014 ml/year faster hippocampal atrophy (95% CI 0.006, 0.022). These contributions were independent and there was no evidence that Aβ and WMHV interacted in their effects. There were no independent associations of APOE ε4 with rates of neurodegeneration after adjusting for Aβ status and WMHV, and no clear relationships between FHS-CVS or systolic BP and rates of neurodegeneration when assessed across the whole sample, nor any evidence that they acted synergistically with Aβ. CONCLUSIONS: Aβ and presumed CVD have distinct and additive effects on rates of neurodegeneration in cognitively normal elderly. These findings have implications for the use of MRI measures as biomarkers of neurodegeneration and emphasize the importance of risk management and early intervention targeting both pathways

Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer’s disease

BACKGROUND: Identifying blood-based signatures of brain health and preclinical pathology may offer insights into early disease mechanisms and highlight avenues for intervention. Here, we systematically profiled associations between blood metabolites and whole-brain volume, hippocampal volume, and amyloid-β status among participants of Insight 46-the neuroscience sub-study of the National Survey of Health and Development (NSHD). We additionally explored whether key metabolites were associated with polygenic risk for Alzheimer's disease (AD). METHODS: Following quality control, levels of 1019 metabolites-detected with liquid chromatography-mass spectrometry-were available for 1740 participants at age 60-64. Metabolite data were subsequently clustered into modules of co-expressed metabolites using weighted coexpression network analysis. Accompanying MRI and amyloid-PET imaging data were present for 437 participants (age 69-71). Regression analyses tested relationships between metabolite measures-modules and hub metabolites-and imaging outcomes. Hub metabolites were defined as metabolites that were highly connected within significant (pFDR < 0.05) modules or were identified as a hub in a previous analysis on cognitive function in the same cohort. Regression models included adjustments for age, sex, APOE genotype, lipid medication use, childhood cognitive ability, and social factors. Finally, associations were tested between AD polygenic risk scores (PRS), including and excluding the APOE region, and metabolites and modules that significantly associated (pFDR < 0.05) with an imaging outcome (N = 1638). RESULTS: In the fully adjusted model, three lipid modules were associated with a brain volume measure (pFDR < 0.05): one enriched in sphingolipids (hippocampal volume: ß = 0.14, 95% CI = [0.055,0.23]), one in several fatty acid pathways (whole-brain volume: ß =  - 0.072, 95%CI = [- 0.12, - 0.026]), and another in diacylglycerols and phosphatidylethanolamines (whole-brain volume: ß =  - 0.066, 95% CI = [- 0.11, - 0.020]). Twenty-two hub metabolites were associated (pFDR < 0.05) with an imaging outcome (whole-brain volume: 22; hippocampal volume: 4). Some nominal associations were reported for amyloid-β, and with an AD PRS in our genetic analysis, but none survived multiple testing correction. CONCLUSIONS: Our findings highlight key metabolites, with functions in membrane integrity and cell signalling, that associated with structural brain measures in later life. Future research should focus on replicating this work and interrogating causality

Operationalizing the centiloid scale for [18F]florbetapir PET studies on PET/MRI

INTRODUCTION: The Centiloid scale aims to harmonize amyloid beta (Aβ) positron emission tomography (PET) measures across different analysis methods. As Centiloids were created using PET/computerized tomography (CT) data and are influenced by scanner differences, we investigated the Centiloid transformation with data from Insight 46 acquired with PET/magnetic resonanceimaging (MRI). METHODS: We transformed standardized uptake value ratios (SUVRs) from 432 florbetapir PET/MRI scans processed using whole cerebellum (WC) and white matter (WM) references, with and without partial volume correction. Gaussian-mixture-modelling-derived cutpoints for Aβ PET positivity were converted. RESULTS: The Centiloid cutpoint was 14.2 for WC SUVRs. The relationship between WM and WC uptake differed between the calibration and testing datasets, producing implausibly low WM-based Centiloids. Linear adjustment produced a WM-based cutpoint of 18.1. DISCUSSION: Transformation of PET/MRI florbetapir data to Centiloids is valid. However, further understanding of the effects of acquisition or biological factors on the transformation using a WM reference is needed

Hippocampal subfield volumes and pre-clinical Alzheimer's disease in 408 cognitively normal adults born in 1946.

BACKGROUND: The human hippocampus comprises a number of interconnected histologically and functionally distinct subfields, which may be differentially influenced by cerebral pathology. Automated techniques are now available that estimate hippocampal subfield volumes using in vivo structural MRI data. To date, research investigating the influence of cerebral β-amyloid deposition-one of the earliest hypothesised changes in the pathophysiological continuum of Alzheimer's disease-on hippocampal subfield volumes in cognitively normal older individuals, has been limited. METHODS: Using cross-sectional data from 408 cognitively normal individuals born in mainland Britain (age range at time of assessment = 69.2-71.9 years) who underwent cognitive assessment, 18F-Florbetapir PET and structural MRI on the same 3 Tesla PET/MR unit (spatial resolution 1.1 x 1.1 x 1.1. mm), we investigated the influences of β-amyloid status, age at scan, and global white matter hyperintensity volume on: CA1, CA2/3, CA4, dentate gyrus, presubiculum and subiculum volumes, adjusting for sex and total intracranial volume. RESULTS: Compared to β-amyloid negative participants (n = 334), β-amyloid positive participants (n = 74) had lower volume of the presubiculum (3.4% smaller, p = 0.012). Despite an age range at scanning of just 2.7 years, older age at time of scanning was associated with lower CA1 (p = 0.007), CA4 (p = 0.004), dentate gyrus (p = 0.002), and subiculum (p = 0.035) volumes. There was no evidence that white matter hyperintensity volume was associated with any subfield volumes. CONCLUSION: These data provide evidence of differential associations in cognitively normal older adults between hippocampal subfield volumes and β-amyloid deposition and, increasing age at time of scan. The relatively selective effect of lower presubiculum volume in the β-amyloid positive group potentially suggest that the presubiculum may be an area of early and relatively specific volume loss in the pathophysiological continuum of Alzheimer's disease. Future work using higher resolution imaging will be key to exploring these findings further

Associations Between Vascular Risk Across Adulthood and Brain Pathology in Late Life: Evidence From a British Birth Cohort.

Importance: Midlife vascular risk burden is associated with late-life dementia. Less is known about if and how risk exposure in early adulthood influences late-life brain health. Objective: To determine the associations between vascular risk in early adulthood, midlife, and late life with late-life brain structure and pathology using measures of white matter-hyperintensity volume, β-amyloid load, and whole-brain and hippocampal volumes. Design, Setting, and Participants: This prospective longitudinal cohort study, Insight 46, is part of the Medical Research Council National Survey of Health and Development, which commenced in 1946. Participants had vascular risk factors evaluated at ages 36 years (early adulthood), 53 years (midlife), and 69 years (early late life). Participants were assessed with multimodal magnetic resonance imaging and florbetapir-amyloid positron emission tomography scans between May 2015 and January 2018 at University College London. Participants with at least 1 available imaging measure, vascular risk measurements at 1 or more points, and no dementia were included in analyses. Exposures: Office-based Framingham Heart study-cardiovascular risk scores (FHS-CVS) were derived at ages 36, 53, and 69 years using systolic blood pressure, antihypertensive medication usage, smoking, diabetic status, and body mass index. Analysis models adjusted for age at imaging, sex, APOE genotype, socioeconomic position, and, where appropriate, total intracranial volume. Main Outcomes and Measures: White matter-hyperintensity volume was generated from T1/fluid-attenuated inversion recovery scans using an automated technique and whole-brain volume and hippocampal volume were generated from automated in-house pipelines; β-amyloid status was determined using a gray matter/eroded subcortical white matter standardized uptake value ratio threshold of 0.61. Results: A total of 502 participants were assessed as part of Insight 46, and 463 participants (236 male [51.0%]) with at least 1 available imaging measure (mean [SD] age at imaging, 70.7 [0.7] years; 83 β-amyloid positive [18.2%]) who fulfilled eligibility criteria were included. Among them, FHS-CVS increased with age (36 years: median [interquartile range], 2.7% [1.5%-3.6%]; 53 years: 10.9% [6.7%-15.6%]; 69 years: 24.3% [14.9%-34.9%]). At all points, these scores were associated with smaller whole-brain volumes (36 years: β coefficient per 1% increase, -3.6 [95% CI, -7.0 to -0.3]; 53 years: -0.8 [95% CI, -1.5 to -0.08]; 69 years: -0.6 [95% CI, -1.1 to -0.2]) and higher white matter-hyperintensity volume (exponentiated coefficient: 36 years, 1.09 [95% CI, 1.01-1.18]; 53 years, 1.02 [95% CI, 1.00-1.04]; 69 years, 1.01 [95% CI, 1.00-1.02]), with largest effect sizes at age 36 years. At no point were FHS-CVS results associated with β-amyloid status. Conclusions and Relevance: Higher vascular risk is associated with smaller whole-brain volume and greater white matter-hyperintensity volume at age 69 to 71 years, with the strongest association seen with early adulthood vascular risk. There was no evidence that higher vascular risk influences amyloid deposition, at least up to age 71 years. Reducing vascular risk with appropriate interventions should be considered from early adulthood to maximize late-life brain health

Increased variability in reaction time is associated with amyloid beta pathology at age 70.

INTRODUCTION: We investigated whether life-course factors and neuroimaging biomarkers of Alzheimer's disease pathology predict reaction time (RT) performance in older adults. METHODS: Insight 46 study participants, all born in the same week in 1946 (n = 501; ages at assessment = 69 to 71 years), completed a 2-choice RT task and amyloid beta (A?) positron emission tomography and MR imaging. We tested for associations between task outcomes (RT; error rate; intra-individual variability in RT) and life-course predictors including childhood cognitive ability and education. In a subsample of 406 cognitively normal participants, we investigated associations between task outcomes and biomarkers including A?-positivity. RESULTS: Cognitively normal A?-positive participants had 10% more variable RTs than A?-negative participants, despite having similar mean RTs. Childhood cognitive ability and education independently predicted task performance. DISCUSSION: This study provides novel evidence that A? pathology is associated with poorer consistency of RT in cognitively normal older adults, at an age when dementia prevalence is still very low