Adiposity and insulin resistance moderate the links between neuroelectrophysiology and working and episodic memory functions in young adult males but not females

INTRODUCTION

Obesity and insulin resistance negatively influence neural activity and cognitive function, but electrophysiological mechanisms underlying these interrelationships remain unclear. This study investigated whether adiposity and insulin resistance moderated neural activity and underlying cognitive functions in young adults.

METHODS

Real-time electroencephalography (EEG) was recorded in 38 lean (n = 12) and obese (n = 26) young adults with (n = 15) and without (n = 23) insulin resistance (18-38 years, 55.3% female) as participants completed three neurocognitive tasks in working memory (Operation Span), inhibitory control (Stroop), and episodic memory (Visual Association Test). Body fat percentage was quantified by a dual-energy X-ray absorptiometry scan (DEXA/DXA). Fasting serum insulin and glucose were quantified to calculate Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) values, for which a higher value indicates more insulin resistance. Hierarchical moderated regression analysis tested these interrelationships.

RESULTS

In males, greater frontal negative slow wave (fNSW) and positive slow wave (PSW) amplitudes were linked to higher working memory accuracy in participants with low, but not high, body fat percentage and HOMA-IR levels. In contrast, body fat percentage and HOMA-IR did not moderate these associations in females. Furthermore, body fat percentage and HOMA-IR values moderated the relationship between greater fNSW amplitudes and better episodic memory accuracy in males, but not females. Finally, body fat percentage and insulin resistance did not moderate the link between neural activity and inhibitory control for either sex.

CONCLUSION

Young adult males, but not females, with higher body adiposity and insulin resistance showed reduced neural activity and worse underlying working and episodic memory functions.

Exploring the secrets of super-aging: a UK Biobank study on brain health and cognitive function

Communities across the globe are faced with a rapidly aging society, where age is the main risk factor for cognitive decline and development of Alzheimer's and related diseases. Despite extensive research, there have been no successful treatments yet. A rare group of individuals called "super-agers" have been noted to thrive with their exceptional ability to maintain a healthy brain and normal cognitive function even in old age. Studying their traits, lifestyles, and environments may provide valuable insight. This study used a data-driven approach to identify potential super-agers among 7121 UK Biobank participants and found that these individuals have the highest total brain volume, best cognitive performance, and lowest functional connectivity. The researchers suggest a novel hypothesis that these super-agers possess enhanced neural processing efficiency that increases with age and introduce a definition of the "neural efficiency index." Furthermore, several other types of aging were identified and significant structural-functional differences were observed between them, highlighting the benefit of research efforts in personalized medicine and precision nutrition.

Beer, wine, and spirits differentially influence body composition in older White adults ‐ a UK Biobank study

BACKGROUND

Aging is characterized by body composition alterations, including increased visceral adiposity accumulation and bone loss. Alcohol consumption may partially drive these alterations, but findings are mixed. This study primarily aimed to investigate whether different alcohol types (beer/cider, red wine, white wine/Champagne, spirits) differentially associated with body composition.

METHODS

The longitudinal UK Biobank study leveraged 1869 White participants (40–80 years; 59% male). Participants self‐reported demographic, alcohol/dietary consumption, and lifestyle factors using a touchscreen questionnaire. Anthropometrics and serum for proteomics were collected. Body composition was obtained via dual‐energy X‐ray absorptiometry. Structural equation modeling was used to probe direct/indirect associations between alcohol types, cardiometabolic biomarkers, and body composition.

RESULTS

Greater beer/spirit consumptions were associated with greater visceral adiposity (β = 0.069, p < 0.001 and β = 0.014, p < 0.001, respectively), which was driven by dyslipidemia and insulin resistance. In contrast, drinking more red wine was associated with less visceral adipose mass (β = −0.023, p < 0.001), which was driven by reduced inflammation and elevated high‐density lipoproteins. White wine consumption predicted greater bone density (β = 0.051, p < 0.005).

DISCUSSION

Beer/spirits may partially contribute to the “empty calorie” hypothesis related to adipogenesis, while red wine may help protect against adipogenesis due to anti‐inflammatory/eulipidemic effects. Furthermore, white wine may benefit bone health in older White adults.1

Food Dietary Choices Predict Brain Volume and Neurovascular Lesion Load 10 Years Later

BACKGROUND

The population age structure in the U.S. is advancing, as to is the prevalence of Alzheimer's disease and related dementias despite life expectancy stagnating in recent years. Decline in neural parameters like brain volume and lesion density are expected with advanced age, but rate and severity of loss and function vary widely. Here, we examined how 149 variables representing the total diet could predict or explain variation in total brain volume and lesion density.

METHODS

Among 10,938 adults aged 45 to 80 from the UK Biobank, food choices for 149 items were measured using the 24-hour Dietary Recall questionnaire and collected up to 5 times over the course of a year. Our outcomes of interest were total brain volume and white matter hyperintensity load, which were derived from a structural Magnetic Resonance Imaging scan conducted 10 years after baseline. Structural equation models of correlated outcomes, using a Backwards selection method (p<.05), were used to identify the most significant food choice predictors.

RESULTS

Over a period of 10 years, more total brain volume was related to consuming more calories in general, water, various coffee preparations, and teas, hard cheeses, whole grain products, pomme fruits like apples and pears, and to some degree various desserts. Conversely, less total brain volume was seen with consuming more red and rose wine, certain vegetables and mushrooms, potatoes, crackers, and beef. For white matter hyperintensities, less lesion load was seen with consuming more mangoes, apiaceae vegetables like carrots and celery, allium vegetables like onions and leeks, spinach, sweet potatoes, and cow's milk of any fat percentage. Conversely, greater lesion load was seen with consuming refined chocolates, processed meats and shellfish, fried potatoes, beets, eggs, mushrooms, and vitamin B6 or calcium supplements.

CONCLUSION

Maintaining brain health was generally related to consuming more water, fruits and vegetables, complex vs. simple carbohydrates, certain sweets, and dairy products while avoiding processed meats, eggs, and mushrooms. Future work will elucidate how whole food choices are related to functional brain imaging outcomes.

Using machine learning to predict COVID-19 infection and severity risk among 4,510 aged adults: a UK Biobank cohort study

BACKGROUND

Many risk factors have emerged for novel 2019 coronavirus disease (COVID-19). It is relatively unknown how these factors collectively predict COVID-19 infection risk, as well as risk for a severe infection (i.e., hospitalization).

METHODS

Among aged adults (69.3 ± 8.6 years) in UK Biobank, COVID-19 data was downloaded for 4,510 participants with 7,539 test cases. We downloaded baseline data from 10-14 years ago, including demographics, biochemistry, body mass, and other factors, as well as antibody titers for 20 common to rare infectious diseases. Permutation-based linear discriminant analysis was used to predict COVID-19 risk and hospitalization risk. Probability and threshold metrics included receiver operating characteristic curves to derive area under the curve (AUC), specificity, sensitivity, and quadratic mean.

RESULTS

The "best-fit" model for predicting COVID-19 risk achieved excellent discrimination (AUC=0.969, 95% CI=0.934-1.000). Factors included age, immune markers, lipids, and serology titers to common pathogens like human cytomegalovirus. The hospitalization "best-fit" model was more modest (AUC=0.803, 95% CI=0.663-0.943) and included only serology titers.

CONCLUSIONS

Accurate risk profiles can be created using standard self-report and biomedical data collected in public health and medical settings. It is also worthwhile to further investigate if prior host immunity predicts current host immunity to COVID-19.

CSF glucose tracks regional tau progression based on Alzheimer's disease risk factors

INTRODUCTION

Glucose hypometabolism and tau formation are key features of Alzheimer's disease (AD). Less is known about the relationship between fasting glucose and regional tau accumulation.

METHODS

Cerebrospinal fluid (CSF) glucose was linearly regressed on regional tau (flortaucipir) among 169 Alzheimer's Disease Neuroimaging Initiative (ADNI3) participants. Flortaucipir uptake was examined by Braak stages and regions of interest (ROIs). Interactions were explored between CSF glucose and AD risk factors including regional amyloid beta (Aβ), sex, Apolipoprotein E ε4 (APOEε4) status, AD parental family history (AD FH), and cognitive impairment (CI).

RESULTS

Interactions found higher CSF glucose tracked less tau in ROIs or Braak stages I/II (women, APOE ε4+, regional Aβ), III/IV (AD FH+, regional Aβ), and V/VI (AD FH+). CI drove Braak III-VI associations.

DISCUSSION

Among women and APOE ε4 carriers, higher CSF glucose tracked less early-stage tau. Higher CSF glucose may reflect compensation against tau spreading in CI, Aβ+, or AD FH+.

Walking in the Light: How History of Physical Activity, Sunlight, and Vitamin D Account for Body Fat-A UK Biobank Study

OBJECTIVE

The high prevalence of vitamin D deficiency and obesity drives the need for successful strategies that elevate vitamin D levels, prevent adipogenesis, and stimulate lipolysis. This study provides a theoretical model to evaluate how physical activity (PA) and sunlight exposure influence serum vitamin D levels and regional adiposity. This study hypothesized a posteriori that sunlight is associated with undifferentiated visceral adiposity by increasing the ratio of brown to white adipose tissue.

METHODS

Using 10-year longitudinal data, accelerometry, a sun-exposure questionnaire, and regional adiposity quantified by dual-energy x-ray absorptiometry imaging, a structural-equation mediation model of growth curves was constructed with a data-driven methodology.

RESULTS

Sunlight and PA conjointly increased serum vitamin D. Changes in vitamin D levels partially mediated how sunlight and PA impacted adiposity in visceral and subcutaneous regions within a subjective PA model. In an objective PA model, vitamin D was a mediator for subcutaneous regions only. Interestingly, sunlight was associated with less adiposity in subcutaneous regions but greater adiposity in visceral regions.

CONCLUSIONS

Sunlight and PA may increase vitamin D levels. For the first time, this study characterizes a positive association between sunlight and visceral adiposity. Further investigation and experimentation are necessary to clarify the physiological role of sunlight exposure on adipose tissue.

Genetic Factors of Alzheimer's Disease Modulate How Diet is Associated with Long-Term Cognitive Trajectories: A UK Biobank Study

BACKGROUND

Fluid intelligence (FI) involves abstract problem-solving without prior knowledge. Greater age-related FI decline increases Alzheimer's disease (AD) risk, and recent studies suggest that certain dietary regimens may influence rates of decline. However, it is uncertain how long-term food consumption affects FI among adults with or without familial history of AD (FH) or APOE4 (ɛ4).

OBJECTIVE

Observe how the total diet is associated with long-term cognition among mid- to late-life populations at-risk and not-at-risk for AD.

METHODS

Among 1,787 mid-to-late-aged adult UK Biobank participants, 10-year FI trajectories were modeled and regressed onto the total diet based on self-reported intake of 49 whole foods from a Food Frequency Questionnaire (FFQ).

RESULTS

Daily cheese intake strongly predicted better FIT scores over time (FH-: β= 0.207, p < 0.001; ɛ4-: β= 0.073, p = 0.008; ɛ4+: β= 0.162, p = 0.001). Alcohol of any type daily also appeared beneficial (ɛ4+: β= 0.101, p = 0.022) and red wine was sometimes additionally protective (FH+: β= 0.100, p = 0.014; ɛ4-: β= 0.59, p = 0.039). Consuming lamb weekly was associated with improved outcomes (FH-: β= 0.066, p = 0.008; ɛ4+: β= 0.097, p = 0.044). Among at risk groups, added salt correlated with decreased performance (FH+: β= -0.114, p = 0.004; ɛ4+: β= -0.121, p = 0.009).

CONCLUSION

Modifying meal plans may help minimize cognitive decline. We observed that added salt may put at-risk individuals at greater risk, but did not observe similar interactions among FH- and AD- individuals. Observations further suggest in risk status-dependent manners that adding cheese and red wine to the diet daily, and lamb on a weekly basis, may also improve long-term cognitive outcomes.

Aging-related changes in fluid intelligence, muscle and adipose mass, and sex-specific immunologic mediation: A longitudinal UK Biobank study

BACKGROUND

Obesity in midlife and early late-life is associated with worse normal cognitive aging. Dual-energy X-ray absorptiometry (DEXA) suggests that visceral adipose mass (VAM) plays a predominant role, whereas non-visceral adipose mass (NVAM) and lean muscle mass (LMM) have shown conflicting relationships. It is unknown how longitudinal, cognitive changes in age-sensitive domains like fluid intelligence (FI) correspond to VAM, NVAM, and LMM in women and men. Furthermore, changes over time in blood leukocyte sub-populations may partially or fully account for sex-specific associations.

METHODS

Data on 4431 late middle-aged, cognitively unimpaired adults (mean = 64.5 y) was obtained from the UK Biobank prospective cohort across 22 centers. FI scores, blood leukocyte counts, and covariates (age, social class, education) were measured at three 2-year intervals over 6 years. DEXA collection overlapped with these intervals. Sex-stratified growth curves, structural equations, and Preacher-Hayes mediation were used to estimate direct and indirect effects. β-weights were standardized.

RESULTS

More LMM predicted gains in FI scores among women (β = 0.130, p < .001) and men (β = 0.089, p < .001). Conversely, more VAM and NVAM independently predicted FI decline equally among sexes (e.g., NVAM: women: β = -0.082, p < .001; men: β = -0.076, p < .001). Among women, FI associations were fully mediated by higher eosinophil counts via VAM (λ = 30.8%, p = .028) and lower lymphocyte counts via LMM (λ = 69.2%, p = .021). Among men, FI associations were partially mediated by lower basophils counts via LMM (λ = 4.5%, p = .042) and higher counts via VAM (λ = 50%, p = .037).

CONCLUSION

The proportion of LMM and VAM equally influenced male FI changes over 6 years, whereas higher LMM among women appeared to more strongly influence. FI changes. Leukocyte counts strongly mediated VAM- and LMM-related FI changes in a sex-specific manner, but not for NVAM. For clinical translation, exercise studies in older adults may benefit from assessing sex-specific values of DEXA-based tissue mass, FI, and leukocyte sub-populations to gauge potential cognitive benefits of less VAM and more LMM.