Search

Abstract Studies of adiposity and cognition’s relationship have been highly mixed, depending on points in the lifespan when adiposity and cognition were measured, primarily with low Black American representation. Therefore, we examined the association between adiposity (from early to mid-life) and mid-life cognition in an Black American (BA) and White American longitudinal cohort to address these literature gaps. The Bogalusa Heart Study has followed participants from childhood to adulthood since 1973. Adiposity was measured via body mass index (BMI) at roughly biannual visits from 1973–2016 and cognition was measured in 1295 participants between 2013- 2016. Cognition included Logical Memory I, II and II Recognition, Digit Spans Forward and Backward, Trail Making Tests A and B, and a global composite. BMI was averaged within age epochs (childhood/adolescence; early adulthood (EA); midlife (M)) with childhood/adolescence BMI as percentiles. Separate linear regression models were run for each cognitive measure (outcome), BMI within one epoch, and sex, race, and education (predictors). All analyses included the 1292 individuals who provided complete data across all epochs. Greater BMI within EA and M was associated with better global cognition (EA: Est. 0.139 S.D./BMI p = 0.000; M: Est. 0.094 S.D./BMI p = 0.022), and Logical Memory I (EA: Est. 0.036 S.D./BMI p = 0.000; M: Est. 0.022 S.D./BMI p = 0.000), II (EA: Est. 0.036 S.D./BMI p = 0.000; M: Est. 0.020 S.D./BMI p = 0.022) and II Recognition (EA: Est. 0.029 S.D./BMI p = 0.000; M: Est. 0.022 S.D./BMI p = 0.000) among men. Among BA, greater BMI within EA and M was associated with better Logical Memory I (EA: Est. 0.022 S.D./BMI p = 0.000; M: Est. 0.019 S.D./BMI p = 0.000) and II (EA: Est. 0.018 S.D./BMI p = 0.042; M: Est. 0.017 S.D./BMI p = 0.000). Greater adiposity from early adulthood to midlife was associated with better memory performance in midlife (associations strongest among men and Black Americans). More anatomically precise measurements of adiposity (e.g., subcutaneous vs. visceral fat) could help clarify the complex adiposity cognition relationship across the lifespan.

While a great deal of recent effort has focused on addressing a perceived reproducibility crisis within brain structural magnetic resonance imaging (MRI) and functional MRI research communities, this article argues that brain positron emission tomography (PET) research stands on even more fragile ground, lagging behind efforts to address MRI reproducibility. We begin by examining the current landscape of factors that contribute to reproducible neuroimaging data analysis, including scientific standards, analytic plan pre-registration, data and code sharing, containerized workflows, and standardized processing pipelines. We then focus on disparities in the current status of these factors between brain MRI and brain PET. To demonstrate the positive impact that further developing such reproducibility factors would have on brain PET research, we present a case study that illustrates the many challenges faced by one laboratory that attempted to reproduce a community-standard brain PET processing pipeline. We identified key areas in which the brain PET community could enhance reproducibility, including stricter reporting policies among PET dedicated journals, data repositories, containerized analysis tools, and standardized processing pipelines. Other solutions such as mandatory pre-registration, data sharing, code availability as a condition of grant funding, and online forums and standardized reporting templates, are also discussed. Bolstering these reproducibility factors within the brain PET research community has the potential to unlock the full potential of brain PET research, propelling it toward a higher-impact future.

IntroductionGlycemic markers throughout life are associated with increased risk of midlife cognitive decline, yet it is unclear whether these associations differ by race and sex.MethodsThis study used cross-sectional analysis of prospectively maintained cohort. 1,295 participants in the Bogalusa Heart Study, a biracial epidemiological cohort located in a micropolitan area core setting, provided fasting plasma insulin (FPI) and glucose (FPG) biannually from 1973 to 2016. Memory, executive function (EF), attention, working memory (WM), and global cognition (GC), collected 2013–2016. Glycemic markers (i.e., FPG, FPI, and HOMA-IR) averaged within lifespan epochs (≤ 20 years, childhood/adolescence (C/A); 21–40 years, early adulthood (EA); and 40–58 years, midlife). Linear regression models were analyzed for each epoch and separate models were analyzed with sex and race, education as a covariate.ResultsSample was 59% women, 34% African American (AA). Among women, higher C/A FPG was associated with poorer memory and poorer GC. Higher EA FPG was associated with poorer WM. Among men, higher EA HOMA-IR was associated with worse attention. Higher C/A HOMA-IR and FPI were associated with better memory, as was higher EA FPI. Among AA, higher C/A FPG was associated with worse attention, EF, and GC. Higher EA HOMA-IR was associated with worse attention. Higher midlife FPI and C/A HOMA-IR were associated with worse WM and EF among White Americans (WAs).DiscussionMarkers indicative of hyperglycemia at different epochs were associated with worse midlife cognition in women, AAs, and WAs; but not in men. Differences in the relationship between lifespan glycemic exposures and midlife cognition could reflect broader health disparities.

IntroductionRegular physical activity lowers risk for cognitive decline and neurodegenerative disorders. Older African Americans (AAs) have been underrepresented in trials that increased physical activity to improve cognitive outcomes.Methods56 sedentary, older, cognitively healthy AAs (avg. 69.2 ± 3.4 yrs. old) were randomized in 1:1 ratio into either a 12-week successful aging group (SAG) or a 12-week physical activity group (PAG). Participants in SAG attended weekly 60-min educational sessions in which healthy aging topics were discussed. Participants in PAG attended supervised physical activity sessions twice per week at local YMCAs (90–120 min/week) and were prescribed 2–3 days per week of home-based activity. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) assessed cognitive function. ANCOVA models compared mean 12-week change in global cognition and subdomain scores between groups with secondary analyses for sex differences. Effect sizes for RBANS were calculated.ResultsThe RBANS global cognition score (SAG Est. 5.6 ± 1.8, effect size = 0.37, p = 0.003) and several subdomain scores (one-sample T tests, all p < 0.05) increased significantly within the SAG. Scores for global cognition increased more in SAG than in PAG (Change Estimate, PAG minus SAG: –4.6 ± 2.5 points, effect size = 0.31) at a trend level (p = 0.072). SAG females increased their global cognition score more than PAG females and more than males in either PAG or SAG (all p < 0.035).DiscussionA 12-week physical activity intervention (PAG) did not improve cognitive functioning among older AAs but a comparator healthy aging education program did. Inadequate physical activity dosage or duration, SAG members acting on health-related information from educational sessions, and/or social stimulation within the SAG may have contributed to these results. Future studies should combine socially engaging activities with vigorous physical activity for cognitive enhancement among cognitively healthy older African Americans.Clinical Trial Registrationwww.ClinicalTrials.gov, identifier NCT03474302.

Abstract Background High levels of sedentary behavior and low physical activity are associated with poor health, and the cognitive determinants of these behaviors in children and adolescents are not well understood. To address this gap, we developed a novel, non-verbal, computer-based assessment to quantify the degree to which youth prefer to be sedentary relative to physically active in their leisure time. Methods The Activity Preference Assessment (APA) uses a forced-choice paradigm to understand implicit decision-making processes when presented with common sedentary and physical activities. The APA bias score ranges from − 100 to + 100, with positive scores indicating a relative preference for sedentary activities, and negative scores representing a preference for physical activities. In 60 children ages 8–17 years, we assessed the validity of this behavioral task against a free-choice play observation, accelerometry-measured activity, anthropometrics and body composition, and cardiorespiratory fitness. We explored neighborhood, family, and individual-level factors that may influence implicit activity preferences. Test-retest reliability was assessed over one week. Results The majority of children (67%) preferred sedentary relative to physical activities. APA bias scores were positively associated with sedentary time during free-choice play. In girls, bias scores were negatively associated with average daily MVPA. APA bias scores were positively associated with body fat and negatively associated with cardiorespiratory fitness. These findings were independent of age, sex, and race/ethnicity. Neighborhood access to physical activity spaces, the number of people in the home, perceived physical self-competence (e.g., coordination, strength), and self-reported depressive symptoms were associated with activity preferences. The intra-class correlation for test-retest reliability was r = 0.59. Conclusions The APA shows promise as a novel tool for quantifying children’s relative preference for sedentary versus physical activities. Implicit bias scores from the APA are clinically meaningful, as shown by significant associations with adiposity and cardiorespiratory fitness. Future longitudinal studies should examine the directionality of the association between preferences and health markers, and the degree to which implicit activity preferences are modifiable. Importantly, the task only takes an average of 10 min to complete, highlighting a potential role as an efficient screening tool for the propensity to be sedentary versus physically active. Trial registration ClinicalTrials.gov NCT03624582 .

Background: Clinical administration of testosterone is widely used due to a variety of claimed physical and cognitive benefits. Testosterone administration is associated with enhanced brain and cognitive function, as well as mood, in energy-balanced males, although such relationships are controversial. However, the effects of testosterone administration on the brains of energy-deficient males, whose testosterone concentrations are likely to be well below normal, have not been investigated. Methods: This study collected functional magnetic resonance imaging (fMRI) data from 50 non-obese young men before (PRE) and shortly after (POST) 28 days of severe exercise-and-diet-induced energy deficit during which testosterone (200 mg testosterone enanthate per week in sesame oil, TEST) or placebo (sesame seed oil only, PLA) were administered. Scans were also collected after a post-energy-deficit weight regain period (REC). Participants completed five fMRI tasks that assessed aspects of: 1) executive function (Attention Network Task or ANT; Multi-Source Interference Task or MSIT; AXE Continuous Processing Task or AXCPT); 2) aggressive behavior (Provoked Aggression Task or AGG); and 3) latent emotion processing (Emotional Face Processing or EMO). Results: Changes over time in task-related fMRI activation in a priori defined task-critical brain regions during performance of 2 out of 5 tasks were significantly different between TEST and PLA, with TEST showing greater levels of activation during ANT in the right anterior cingulate gyrus at POST and during MSIT in several brain regions at REC. Changes over time in objective task performance were not statistically significant; testosterone-treated volunteers had greater self-reported anger during AGG at POST. Conclusions: Testosterone administration can alter some aspects of brain function during severe energy deficit and increase levels of anger.

Background: Severe energy deficits during military operations, produced by significant increases in exercise and limited dietary intake, result in conditions that degrade lean body mass and lower-body muscle function, which may be mediated by concomitant reductions in circulating testosterone. Methods: We conducted a three-phase, proof-of-concept, single centre, randomised, double-blind, placebo-controlled trial (CinicalTrials.gov, NCT02734238) of non-obese men: 14-d run-in, free-living, eucaloric diet phase; 28-d live-in, 55% exercise- and diet-induced energy deficit phase with (200 mg testosterone enanthate per week, Testosterone, n = 24) or without (Placebo, n = 26) exogenous testosterone; and 14-d recovery, free-living, ad libitum diet phase. Body composition was the primary end point; secondary endpoints included lower-body muscle function and health-related biomarkers. Findings: Following energy deficit, lean body mass increased in Testosterone and remained stable in Placebo, such that lean body mass significantly differed between groups [mean difference between groups (95% CI), 2.5 kg (3.3, 1.6); P

Prior research has suggested that measurements of brain functioning and performance on dual tasks (tasks which require simultaneous performance) are promising candidate predictors of fall risk among older adults. However, no prior study has investigated whether brain function measurements during dual task performance could improve prediction of fall risks and whether the type of subtasks used in the dual task paradigm affects the strength of the association between fall characteristics and dual task performance. In this study, 31 cognitively normal, community-dwelling older adults provided a self-reported fall profile (number of falls and fear of falling), completed a gait dual task (spell a word backward while walking on a GaitRite mat), and completed a supine dual task (rhythmic finger tapping with one hand while completing the AX continuous performance task (AX-CPT) with the other hand) during functional magnetic resonance imaging (fMRI). Gait performance, AX-CPT reaction time and accuracy, finger tapping cadence, and brain functioning in finger-tapping-related and AX-CPT-related brain regions all showed declines in the dual task condition compared to the single task condition. Dual-task gait, AX-CPT and finger tapping performance, and brain functioning were all independent predictors of fall profile. No particular measurement domain stood out as being the most strongly associated measure with fall variables. Fall characteristics are determined by multiple factors; brain functioning, motor task, and cognitive task performance in challenging dual-task conditions all contribute to the risk of falling.

Introduction: White matter hyperintensities (WMHs) are areas of abnormal signal on magnetic resonance images (MRIs) that characterize various types of histopathological lesions. The load and location of WMHs are important clinical measures that may indicate the presence of small vessel disease in aging and Alzheimer's disease (AD) patients. Manually segmenting WMHs is time consuming and prone to inter-rater and intra-rater variabilities. Automated tools that can accurately and robustly detect these lesions can be used to measure the vascular burden in individuals with AD or the elderly population in general. Many WMH segmentation techniques use a classifier in combination with a set of intensity and location features to segment WMHs, however, the optimal choice of classifier is unknown. Methods: We compare 10 different linear and nonlinear classification techniques to identify WMHs from MRI data. Each classifier is trained and optimized based on a set of features obtained from co-registered MR images containing spatial location and intensity information. We further assess the performance of the classifiers using different combinations of MRI contrast information. The performances of the different classifiers were compared on three heterogeneous multi-site datasets, including images acquired with different scanners and different scan-parameters. These included data from the ADC study from University of California Davis, the NACC database and the ADNI study. The classifiers (naïve Bayes, logistic regression, decision trees, random forests, support vector machines, k-nearest neighbors, bagging, and boosting) were evaluated using a variety of voxel-wise and volumetric similarity measures such as Dice Kappa similarity index (SI), Intra-Class Correlation (ICC), and sensitivity as well as computational burden and processing times. These investigations enable meaningful comparisons between the performances of different classifiers to determine the most suitable classifiers for segmentation of WMHs. In the spirit of open-source science, we also make available a fully automated tool for segmentation of WMHs with pre-trained classifiers for all these techniques. Results: Random Forests yielded the best performance among all classifiers with mean Dice Kappa (SI) of 0.66±0.17 and ICC=0.99 for the ADC dataset (using T1w, T2w, PD, and FLAIR scans), SI=0.72±0.10, ICC=0.93 for the NACC dataset (using T1w and FLAIR scans), SI=0.66±0.23, ICC=0.94 for ADNI1 dataset (using T1w, T2w, and PD scans) and SI=0.72±0.19, ICC=0.96 for ADNI2/GO dataset (using T1w and FLAIR scans). Not using the T2w/PD information did not change the performance of the Random Forest classifier (SI=0.66±0.17, ICC=0.99). However, not using FLAIR information in the ADC dataset significantly decreased the Dice Kappa, but the volumetric correlation did not drastically change (SI=0.47±0.21, ICC=0.95). Conclusion: Our investigations showed that with appropriate features, most off-the-shelf classifiers are able to accurately detect WMHs in presence of FLAIR scan information, while Random Forests had the best performance across all datasets. However, we observed that the performances of most linear classifiers and some nonlinear classifiers drastically decline in absence of FLAIR information, with Random Forest still retaining the best performance.

Food image fMRI paradigms are used widely for investigating the neural basis of ingestive behavior. However, these paradigms have not been validated in terms of ingestive behavior constructs, engagement of food-relevant neural systems, or test-retest reliability, making the generalizability of study findings unclear. Therefore, we validated the Macronutrient Picture System (MaPS) (McClernon et al., 2013), which includes food images from the six categories represented in the Geiselman Food Preference Questionnaire (FPQ) (Geiselman et al., 1998). Twenty-five healthy young adults (n = 21 female, mean age = 20.6 ± 1.1 years, mean BMI = 22.1 ± 1.9 kg/m2) rated the MaPS images in terms of visual interest, appetitive quality, nutrition, emotional valence, liking, and frequency of consumption, and completed the FPQ. In a second study, 12 individuals (n=8 female, mean age = 25.0 ± 6.5 years, mean BMI = 28.2 ± 8.7 kg/m2) viewed MaPS and control images (vegetables and non-food) during two separate 3T BOLD fMRI scans after fasting overnight. Intuitively, high fat/high sugar (HF/HS) and high fat/high complex carbohydrate (HF/HCCHO) images achieved higher liking and appetitive ratings, and lower nutrition ratings, than low fat/low complex carbohydrate/high protein (LF/LCHO/HP) images on average. Within each food category, FPQ scores correlated strongly with MaPS image liking ratings (p < 0.001). Brain activation differences between viewing images of HF/HS and vegetables, and between HF/HCCHO and vegetables, were seen in several reward-related brain regions (e.g., putamen, insula, and medial frontal gyrus). Intra-individual, inter-scan agreement in a summary measure of brain activation differences in seven reward network regions of interest was high (ICC = 0.61), and was even higher when two distinct sets of food images with matching visual ratings were shown in the two scans (ICC = 0.74). These results suggest that the MaPS provides valid representation of food categories and reliably activates food-reward-relevant neural systems.

Stimulating increased thermogenic activity in adipose tissue is an important biological target for obesity treatment, and label-free imaging techniques with the potential to quantify stimulation-associated biochemical changes to the adipose tissue are highly sought after. In this study, we used spatially resolved Fourier transform infrared (FTIR) imaging to quantify biochemical changes caused by cold exposure in the brown and subcutaneous white adipose tissues (BAT and s-WAT) of 6 week-old C57BL6 mice exposed to 30°C (N = 5), 24°C (N = 5), and 10°C (N = 5) conditions for 10 days. Fat exposed to colder temperatures demonstrated greater thermogenic activity as indicated by increased messenger RNA expression levels of a panel of thermogenic marker genes including uncoupling protein 1 (UCP-1) and Dio2. Protein to lipid ratio, calculated from the ratio of the integrated area from 1,600 to 1,700 cm−1 (amide I) to the integrated area from 2,830 to 2,980 cm−1 (saturated lipids), was elevated in 10°C BAT and s-WAT compared to 24°C (p = 0.004 and p