Erratum to: Association between Modifiable Risk Factors and Levels of Blood-Based Biomarkers of Alzheimer's and Related Dementias in the Look AHEAD Cohort.

[This corrects the article DOI: 10.14283/jarlife.2024.1.].

Association between Modifiable Risk Factors and Levels of Blood-Based Biomarkers of Alzheimer's and Related Dementias in the Look AHEAD Cohort.

Background: Emerging evidence suggests that a number of factors can influence blood-based biomarker levels for Alzheimer's disease (AD) and Alzheimer's related dementias (ADRD). We examined the associations that demographic and clinical characteristics have with AD/ADRD blood-based biomarker levels in an observational continuation of a clinical trial cohort of older individuals with type 2 diabetes and overweight or obesity. Methods: Participants aged 45-76 years were randomized to a 10-year Intensive Lifestyle Intervention (ILI) or a diabetes support and education (DSE) condition. Stored baseline and end of intervention (8-13 years later) plasma samples were analyzed with the Quanterix Simoa HD-X Analyzer. Changes in Aß42, Aß40, Aß42/Aß40, ptau181, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were evaluated in relation to randomization status, demographic, and clinical characteristics. Results: In a sample of 779 participants from the Look AHEAD cohort, we found significant associations between blood-based biomarkers for AD/ADRD and 15 of 18 demographic (age, gender, race and ethnicity, education) and clinical characteristics (APOE, depression, alcohol use, smoking, body mass index, HbA1c, diabetes duration, diabetes treatment, estimated glomerular filtration rate, hypertension, and history of cardiovascular disease) . Conclusions: Blood-based biomarkers of AD/ADRD are influenced by common demographic and clinical characteristics. These factors should be considered carefully when interpreting these AD/ADRD blood biomarker values for clinical or research purposes.

A Combination of Essential Fatty Acids, Panax Ginseng Extract, and Green Tea Catechins Modifies Brain fMRI Signals in Healthy Older Adults.

OBJECTIVES: To assess the effects of a combination of omega 3 essential fatty acids, green tea catechins, and ginsenosides on cognition and brain functioning in healthy older adults. DESIGN: Double-blind, placebo-controlled, crossover design randomized controlled trial with 26-day intervention phases and a 30-day washout period. SETTING: The Institute for Dementia Research and Prevention at the Pennington Biomedical Research Center. PARTICIPANTS: Ten independently-living, cognitively-healthy older adults (mean age: 67.3 + 2.01 years). INTERVENTION: Daily consumption of an investigational product (trade name "Cerbella TM") consisting of an emulsified liquid combination of standardized fish oil, panax ginseng extract, and green tea catechins in a flavored base of lecithin phospholipids optimized to maximize bioavailability of the active ingredients. MEASUREMENTS: Before and after supplementation with the investigational product or placebo, participants completed cognitive tests including the Mini Mental State Exam (MMSE), Stroop test, Digit Symbol Substitution Test (DSST), and Immediate and Delayed Recall tests, as well as functional magnetic resonance imaging (fMRI) during a standard cognitive task switching paradigm. RESULTS: Performance on the MMSE, Stroop test, and DSST increased significantly over one month of supplementation with the investigational product (one-sample t tests, p<.05) although differences between these changes and corresponding changes during supplementation with placebo were not significant (two-sample t tests, p>.05). During supplementation with the investigational product, brain activation during task performance increased significantly more than during supplementation with placebo in brain regions known to be activated by this task (anterior and posterior cingulate cortex). Functional connectivity during task execution between task regions (middle frontal gyrus and anterior cingulate cortex) increased significantly during supplementation with the investigational product, relative to placebo. Functional connectivity during rest between task regions (precentral gyrus and middle frontal gyrus) and default mode network regions (medial frontal gyrus and precuneus) decreased during supplementation with the investigational product relative to placebo, suggesting greater segregation of task and rest related brain activity. CONCLUSION: One-month supplementation with a combination of omega 3 essential fatty acids, green tea catechins, and ginsenosides was associated with suggestive changes in cognitive functioning as well as modification of brain activation and brain functional connectivity in cognitively healthy older adults.

Resting state functional connectivity is associated with cognitive dysfunction in non-demented people with Parkinson's disease.

BACKGROUND: Parkinson's disease (PD) can result in cognitive impairment. Executive dysfunction often appears early, followed by more widespread deficits later in the course of the disease. Disruption of parallel basal ganglia thalamo-cortical loops that subserve motor and cognitive function has been described in PD. However, there is emerging evidence that the default mode network, a cortical network that is active at rest with reduced activation during task performance, may also play a role in disease related cognitive decline. OBJECTIVE: To determine the relative contribution of the executive control and default mode networks to parkinsonian executive dysfunction in medicated non-demented patients. METHODS: We used BOLD fMRI to measure resting state functional connectivity in the executive control and default mode (DM) networks, and examined switching, processing speed, working memory/attention and motor performance in 14 medicated non-demented PD participants and 20 controls. RESULTS: Performance on neuropsychological measures was similar across groups. Functional connectivity was not different across disease conditions in the executive control network. DMN functional connectivity was decreased in the PD group, specifically between posterior cingulate, medial prefrontal, and inferior parietal nodes. Greater DMN functional connectivity was associated with faster processing speed in the PD group. CONCLUSIONS: The continuous relationship between DMN disconnection and executive task performance indicates a possible biological contributor to parkinsonian cognitive deficits. The dynamics of executive control network change may be different than that of the DMN, suggesting less sensitivity to early cognitive deficits.

FLAIR and diffusion MRI signals are independent predictors of white matter hyperintensities.

BACKGROUND AND PURPOSE: WMH, associated with cognitive decline and cardiovascular risk factors, may represent only the extreme end of a more widespread continuous WM injury process that progresses during aging and is poorly understood. We investigated the ability of FLAIR and DTI to characterize the longitudinal course of WMH development. MATERIALS AND METHODS: One hundred nineteen participants (mean age, 74.5 ± 7.4), including cognitively healthy elders and subjects diagnosed with Alzheimer disease and mild cognitive impairment, received a comprehensive clinical evaluation and brain MR imaging, including FLAIR and DTI on 2 dates. The risk for each baseline normal-appearing WM voxel to convert into WMH was modeled as a function of baseline FA (model M1) and both baseline FA and standardized FLAIR (M2). Sensitivity, specificity, accuracy, and AUC for predicting conversion to WMH were compared between models. RESULTS: Independent of clinical diagnosis, lower baseline FA (P < .001, both models) and higher baseline FLAIR intensity (P < .001, M2) were independently associated with increased risk for conversion from normal WM to WMH. M1 exhibited higher sensitivity but lower specificity, accuracy, and AUC compared with M2. CONCLUSIONS: These findings provide further evidence that WMH result from a continuous process of WM degeneration with time. Stepwise decreases in WM integrity as measured by both DTI and FLAIR were independently associated with stepwise increases in WMH risk, emphasizing that these modalities may provide complementary information for understanding the time course of aging-associated WM degeneration.

The contributions of MRI-based measures of gray matter, white matter hyperintensity, and white matter integrity to late-life cognition.

BACKGROUND AND PURPOSE: GM volume, WMH volume, and FA are each associated with cognition; however, few studies have detected whether these 3 different types of MR imaging measurements exert independent or additive effects on cognitive performance. To detect their extent of contribution to cognitive performance, we explored the independent and additive contributions of GM atrophy, white matter injury, and white matter integrity to cognition in elderly patients. MATERIALS AND METHODS: Two hundred and 9 elderly patients participated in the study: 97 were CN adults, 65 had MCI, and 47 had dementia. We measured GM on T1-weighted MR imaging, WMH on FLAIR, and FA on DTI, along with psychometrically matched measures of 4 domains of cognitive performance, including semantic memory, episodic memory, executive function, and spatial abilities. RESULTS: As expected, patients with dementia performed significantly more poorly in all 4 cognitive domains, whereas patients with MCI performed generally less poorly than dementia patients, though considerable overlap in performance was present across groups. GM, FA, and WMH each differed significantly between diagnostic groups and were associated with cognitive measures. In multivariate models that included all 3 MR imaging measures (GM, WMH, and FA), GM volume was the strongest determinant of cognitive performance. CONCLUSIONS: These results strongly suggest that MR imaging measures of GM are more closely associated with cognitive function than WM measures across a broad range of cognitive and functional impairment.

MRI non-uniformity correction through interleaved bias estimation and B-spline deformation with a template.

We propose a template-based method for correcting field inhomogeneity biases in magnetic resonance images (MRI) of the human brain. At each algorithm iteration, the update of a B-spline deformation between an unbiased template image and the subject image is interleaved with estimation of a bias field based on the current template-to-image alignment. The bias field is modeled using a spatially smooth thin-plate spline interpolation based on ratios of local image patch intensity means between the deformed template and subject images. This is used to iteratively correct subject image intensities which are then used to improve the template-to-image deformation. Experiments on synthetic and real data sets of images with and without Alzheimer's disease suggest that the approach may have advantages over the popular N3 technique for modeling bias fields and narrowing intensity ranges of gray matter, white matter, and cerebrospinal fluid. This bias field correction method has the potential to be more accurate than correction schemes based solely on intrinsic image properties or hypothetical image intensity distributions.

Subtypes based on cerebrospinal fluid and magnetic resonance imaging markers in normal elderly predict cognitive decline.

Cerebrospinal fluid (CSF) and structural magnetic resonance imaging (MRI) show patterns of change in Alzheimer's disease (AD) that precede dementia. The Alzheimer's Disease Neuroimaging Initiative (ADNI) studied normal controls (NC), subjects with mild cognitive impairment (MCI), and subjects with AD to identify patterns of biomarkers to aid in early diagnosis and effective treatment of AD. Two hundred twenty-two NC underwent baseline MRI and clinical examination at baseline and at least one follow-up. One hundred twelve also provided CSF at baseline. Unsupervised clustering based on initial CSF and MRI measures was used to identify clusters of participants with similar profiles. Repeated measures regression modeling assessed the relationship of individual measures, and of cluster membership, to cognitive change over 3 years. Most individuals showed little cognitive change. Individual biomarkers had limited predictive value for cognitive decline, but membership in the cluster with the most extreme profile was associated with more rapid decline in ADAS-cog. Subtypes among NC based on multiple biomarkers may represent the earliest stages of subclinical cognitive decline and AD.

Age, Alzheimer disease, and brain structure.

BACKGROUND: Lack of clear understanding remains on the overlapping atrophy patterns of aging and early Alzheimer disease (AD) pathology in gray matter (GM) of the brain in vivo. OBJECTIVE: To evaluate the independent and overlapping patterns of GM atrophy in normal aging and AD. METHODS: A total of 169 cognitively normal subjects and 33 persons with probable AD enrolled in the longitudinal Cardiovascular Health Study-Cognition Study underwent 3-dimensional volumetric MRI scans. Controls remained cognitively normal for at least 5 years after their MRI scans and the probable AD subjects were relatively early in their clinical course with an average modified Mini-Mental State Examination score of 76/100. The scans were analyzed using voxel-based morphometry adjusting for total intracranial volume, gender, education, and race. RESULTS: With older age, GM volume was lower in the sensorimotor and heteromodal association areas in frontal, temporal, occipital, and parietal lobes, as well as in the cerebellum (false discovery rate p = 0.05). Additional atrophy was observed in the posterior hippocampus, thalamus, and middle cingulate gyrus. By contrast, atrophy was seen in subjects with AD in the anterior hippocampal/parahippocampal regions and the precuneus. Normal aging and AD overlapped in the hippocampal body and the entorhinal cortex. CONCLUSION: Brain atrophy with aging was observed in supratentorial and infratentorial areas, as well in primary motor, sensory, and heteromodal association regions. Age and Alzheimer disease exert independent gray matter atrophy patterns but these effects overlapped substantially in the hippocampus and entorhinal cortex.

Regional pattern of white matter microstructural changes in normal aging, MCI, and AD.

OBJECTIVE: To cross-sectionally compare the regional white matter fractional anisotropy (FA) of cognitively normal (CN) older individuals and patients with mild cognitive impairment (MCI) and Alzheimer disease (AD), separately focusing on the normal-appearing white matter (NAWM) and white matter hyperintensities (WMH), and to test the independent effects of presumed degenerative and vascular process on FA differences. METHODS: Forty-seven patients with AD, 73 patients with MCI, and 95 CN subjects received diffusion tensor imaging and vascular risk evaluation. To properly control normal regional variability of FA, we divided cerebral white matter into 4 strata as measured from a series of young healthy individuals (H1 = highest; H2 = intermediate high; H3 = intermediate low; H4 = lowest anisotropy stratum). RESULTS: For overall cerebral white matter, patients with AD had significantly lower FA than CN individuals or patients with MCI in the regions with higher baseline anisotropy (H1, H2, and H3), corresponding to long corticocortical association fibers, but not in H4, which mostly includes heterogeneously oriented fibers. Vascular risk showed significant independent effects on FA in all strata except H1, which corresponds to the genu and splenium of the corpus callosum. Similar results were found within NAWM. FA in WMH was significantly lower than NAWM across all strata but was not associated with diagnosis or vascular risk. CONCLUSIONS: Both vascular and Alzheimer disease degenerative process contribute to microstructural injury of cerebral white matter across the spectrum of cognitive ability and have different region-specific injury patterns.