Abstract Introduction Amyloid beta (Aβ), tau, and neurodegeneration jointly with the Alzheimer's disease (AD) risk factors affect the severity of clinical symptoms and disease progression. Methods Within 248 Aβ‐positive elderly with and without cognitive impairment and dementia, partial least squares structural equation pathway modeling was used to assess the direct and indirect effects of imaging biomarkers (global Aβ‐positron emission tomography [PET] uptake, regional tau‐PET uptake, and regional magnetic resonance imaging–based atrophy) and risk‐factors (age, sex, education, apolipoprotein E [ APOE ], and white‐matter lesions) on cross‐sectional cognitive impairment and longitudinal cognitive decline. Results Sixteen percent of variance in cross‐sectional cognitive impairment was accounted for by Aβ, 46% to 47% by tau, and 25% to 29% by atrophy, although 53% to 58% of total variance in cognitive impairment was explained by incorporating mediated and direct effects of AD risk factors. The Aβ–tau–atrophy pathway accounted for 50% to 56% of variance in longitudinal cognitive decline while Aβ, tau, and atrophy independently explained 16%, 46% to 47%, and 25% to 29% of the variance, respectively. Discussion These findings emphasize that treatments that remove Aβ and completely stop downstream effects on tau and neurodegeneration would only be partially effective in slowing of cognitive decline or reversing cognitive impairment.
APOE3
-Jacksonville (V236E) variant reduces self-aggregation and risk of dementia
AbstractIntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020.MethodsWe identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion.ResultsDisease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity.DiscussionADNI has had a profound impact in improving clinical trials for AD.
Associations of amyloid and neurodegeneration plasma biomarkers with comorbidities
AbstractIntroductionBlood‐based biomarkers of amyloid pathology and neurodegeneration are entering clinical use. It is critical to understand what factors affect the levels of these markers.MethodsPlasma markers (Aβ42, Aβ40, NfL, T‐tau, Aβ42/40 ratio) were measured on the Quanterix Simoa HD‐1 analyzer for 996 Mayo Clinic Study of Aging (MCSA) participants, aged 51 to 95 years. All other data were collected during in‐person MCSA visits or abstracted from the medical record.ResultsAmong cognitively unimpaired (CU) participants, all plasma markers correlated with age. Linear regression models revealed multiple relationships. For example, higher Charlson Comorbidity Index and chronic kidney disease were associated with higher levels of all biomarkers. Some relationships differed between mild cognitive impairment and dementia participants.DiscussionMultiple variables affect plasma biomarkers of amyloid pathology and neurodegeneration among CU in the general population. Incorporating this information is critical for accurate interpretation of the biomarker levels and for the development of reference ranges.
Cerebral Amyloid Angiopathy Pathology and Its Association With Amyloid-β PET Signal
Background White matter abnormalities are a common feature of aging and Alzheimer disease, and tend to be more severe among Black individuals. However, the extent to which white matter abnormalities relate to amyloid deposition, a marker of Alzheimer pathology, remains unclear. This cross‐sectional study examined the association of white matter abnormalities with cortical amyloid in a community sample of older adults without dementia and examined the moderating effect of race. Methods and Results Participants from the ARIC‐PET (Atherosclerosis Risk in Communities‐Positron Emission Tomography) study underwent brain magnetic resonance imaging, which quantified white matter hyperintensity volume and microstructural integrity using diffusion tensor imaging. Participants received florbetapir positron emission tomography imaging to measure brain amyloid. Associations between measures of white matter structure and elevated amyloid status were examined using multivariable logistic regression. Among 322 participants (43% Black), each SD increase in white matter hyperintensity volume was associated with a greater odds of elevated amyloid (odds ratio [OR], 1.37; 95% CI, 1.03–1.83) after adjusting for demographic and cardiovascular risk factors. In race‐stratified analyses, a greater white matter hyperintensity volume was more strongly associated with elevated amyloid among Black participants (OR, 2.00; 95% CI, 1.15–3.50), compared with White participants (OR, 1.29; 95% CI, 0.89–1.89). However, the race interaction was not statistically significant ( P interaction=0.09). We found no association between white matter microstructure and elevated amyloid. Conclusions The results suggest a modest positive relationship between white matter hyperintensity and elevated amyloid in older adults without dementia. Although the results indicate that this association is nonsignificantly stronger among Black participants, these findings will need to be confirmed or refuted using larger multiracial cohorts.
Deep learning-based brain age prediction in normal aging and dementia
Abstract Normal brain aging is accompanied by patterns of functional and structural change. Alzheimer's disease (AD), a representative neurodegenerative disease, has been linked to accelerated brain aging at respective age ranges. Here, we developed a deep learning-based brain age prediction model using fluorodeoxyglucose (FDG) PET and structural MRI and tested how the brain age gap relates to degenerative cognitive syndromes including mild cognitive impairment, AD, frontotemporal dementia, and Lewy body dementia. Occlusion analysis, performed to facilitate interpretation of the model, revealed that the model learns an age- and modality-specific pattern of brain aging. The elevated brain age gap in dementia cohorts was highly correlated with the cognitive impairment and AD biomarker. However, regions generating brain age gaps were different for each diagnosis group of which the AD continuum showed similar patterns to normal aging in the CU.
Chronic Kidney Disease Associated with Worsening White Matter Disease and Ventricular Enlargement
Background: Chronic kidney disease (CKD), a growing public health issue in the elderly, is associated with increased risk of cognitive impairment. Objective: To investigate the mechanisms through which CKD impacts brain health using longitudinal imaging. Methods: We identified 97 participants (74 CKD and 23 non-CKD) from the BRINK (BRain IN Kidney Disease), a longitudinal study of CKD with two MRI scans (baseline and 3-year follow-up). We measured the associations between baseline and change in kidney disease biomarkers of estimated glomerular filtration rate (eGFR) and urinary albumin to creatinine ratio (UACR), considered a measure of microvascular inflammation, and imaging outcomes of cortical thickness and ventricular volume from structural MRI, white matter hyperintensities (WMH) volume from FLAIR images, and fractional anisotropy of the corpus callosum (FACC). Results: There were white matter-specific changes as observed by increased WMH volume and decreased FACC in CKD participants, as well as ventricular volume increase in both CKD and non-CKD groups reflective of aging-related changes. Decline in eGFR was associated with decrease in the FACC, suggesting that subtle early white matter changes due to kidney disease can be captured using DTI. An increase in UACR was associated with increase in ventricular volume. Conclusion: Our results support the role of eGFR as a measure of kidney microvascular disease which is associated with concurrent white matter damage in CKD. Future work is needed to investigate the possible link between endothelial microvascular inflammation (as measured by an increased UACR) and ventricular volume increase.
Gray and White Matter Correlates of Dysphagia in Progressive Supranuclear Palsy