Higher visceral fat is associated with lower cerebral N-acetyl-aspartate ratios in middle-aged adults

Lower Body Mass Index at Baseline Is Related to Steeper Cognitive Decline in the Alzheimer's Disease Neuroimaging Initiative Cohort

OBJECTIVE

Midlife obesity is a risk factor for dementia, whereas obesity in older age may be protective of cognition, a phenomenon known as the "obesity paradox." The mechanisms underlying this phenomenon and the relationship between body mass index (BMI) and cognitive function over time remain unclear.

METHODS

In 1399 adults with and without mild cognitive impairment (median age 73.6 years) from the Alzheimer's Disease Neuroimaging Initiative, we modeled the effects of baseline BMI on within-person trajectories of cognitive decline using Latent Growth Curve Modeling. We also tested if the effects of BMI on cognitive decline are global or specific to memory, executive function, or language.

RESULTS

Higher baseline BMI was associated with better memory ( βBMI = 0.06, p < .05) and worse executive function ( βBMI = -0.05, p < .05) and not associated with language. Independent of baseline diagnosis, higher baseline BMI was associated with slower rate of decline in executive function, memory, and language ( βBMI = 0.13, 0.12, and 0.12, respectively; p < .01). Higher BMI was not associated with the intercept ( βBMI = 0.04, p = .059) or change ( βBMI = 0.04, p = .415) in a global cognitive factor.

CONCLUSIONS

We found that higher baseline BMI was associated with slower cognitive decline in participants with and without mild cognitive impairment diagnosis. Higher BMI in this context seems to be protective of cognitive function for people at risk for dementia. Our findings also support domain-specific effects of obesity on various cognitive functions rather than a final common pathway.

Inverse Association Between Hypothalamic N-Acetyl Aspartate/Creatine Ratio and Indices of Body Mass in Adolescents with Obesity

BACKGROUND

Approximately 10% of adolescents worldwide are overweight or obese, hence the urgent and universal need to elucidate possible mechanisms that lead to obesity in the adolescent population.

OBJECTIVES

We examined the hypothalamic metabolism and its relationship with physical development in obese and eutrophic adolescents.

METHODS

We performed a case-control study with 115 adolescents between 11 and 18 years of age, to compare obese (BMI z-score ≥ 2) and nonobese individuals (eutrophic controls; BMI z-score ≤ 1). The following hypothalamic metabolite ratios were examined as primary outcomes: glutamate/creatine (Cr), the sum of glutamate and glutamine/Cr, N-acetylaspartate (NAA)/Cr, myoinositol/Cr, and total choline/Cr (glycerophosphocholine +  phosphocholine/Cr), quantified by magnetic resonance spectroscopy. BMI z-scores, pubertal status, and scores on the Yale Food Addiction Scale, the Binge Eating Scale, and the Child Depression Inventory were assessed as secondary outcomes. Pearson coefficients (r) or nonparametric Spearman correlation (rho) analyses were performed between hypothalamic metabolite ratios and other parameters, such as BMI z-scores, physical development, food habits, depression symptoms, and serum protein concentrations (cytokines, hormones, and neuropeptides).

RESULTS

Adolescents with obesity showed a lower hypothalamic NAA/Cr ratio (0.70 ± 0.19) compared to their eutrophic counterparts (0.84 ± 0.20; P = 0.004). The NAA/Cr ratio was negatively correlated with BMI z-scores (r = -0.25; P = 0.03) and serum insulin (rho = -0.27; P = 0.04), C-peptide (rho = -0.26; P = 0.04), amylin (r = -0.27; P = 0.04), ghrelin (rho = -0.30; P = 0.02), and neuropeptide Y (r = -0.27; P = 0.04). Also, the NAA/Cr ratio was positively correlated with circulating IL-8 levels (rho = 0.26; P = 0.04).

CONCLUSIONS

High BMI z-scores are associated with lower hypothalamic NAA/Cr ratios. The negative correlations found between the NAA/Cr ratio and serum cytokines, hormones, and neuropeptides suggest a broad cross-talk linking hormonal imbalances, neurohumoral alterations, and hypothalamic functions in adolescents with obesity.

Network Modeling Sex Differences in Brain Integrity and Metabolic Health

Hypothesis-driven studies have demonstrated that sex moderates many of the relationships between brain health and cardiometabolic disease, which impacts risk for later-life cognitive decline. In the present study, we sought to further our understanding of the associations between multiple markers of brain integrity and cardiovascular risk in a midlife sample of 266 individuals by using network analysis, a technique specifically designed to examine complex associations among multiple systems at once. Separate network models were constructed for male and female participants to investigate sex differences in the biomarkers of interest, selected based on evidence linking them with risk for late-life cognitive decline: all components of metabolic syndrome (obesity, hypertension, dyslipidemia, and hyperglycemia); neuroimaging-derived brain-predicted age minus chronological age; ratio of white matter hyperintensities to whole brain volume; seed-based resting state functional connectivity in the Default Mode Network, and ratios of N-acetyl aspartate, glutamate and myo-inositol to creatine, measured through proton magnetic resonance spectroscopy. Males had a sparse network (87.2% edges = 0) relative to females (69.2% edges = 0), indicating fewer relationships between measures of cardiometabolic risk and brain integrity. The edges in the female network provide meaningful information about potential mechanisms between brain integrity and cardiometabolic health. Additionally, Apolipoprotein ϵ4 (ApoE ϵ4) status and waist circumference emerged as central nodes in the female model. Our study demonstrates that network analysis is a promising technique for examining relationships between risk factors for cognitive decline in a midlife population and that investigating sex differences may help optimize risk prediction and tailor individualized treatments in the future.

Body mass and cardiorespiratory fitness are associated with altered brain metabolism

Magnetic Resonance Spectroscopy provides measures of brain chemistry that are sensitive to cardiorespiratory fitness and body composition. The concentration of N-acetyl aspartic acid (NAA) is of interest because it is a marker of neuronal integrity. The ratio of NAA to creatine, a standard reference metabolite, has been shown to correlate with measures of both cardiorespiratory fitness and body composition. However, previous studies have explored these effects in isolation, making it impossible to know which of these highly correlated measures drive the correlations with NAA/Cr. As a result, the mechanisms underlying their association remain to be established. We therefore conducted a comprehensive study to investigate the relative contributions of cardiorespiratory fitness and percent body fat in predicting NAA/Cr. We demonstrate that NAA/Cr in white matter is correlated with percent body fat, and that this relationship largely subsumes the correlation of NAA/Cr with cardiorespiratory fitness. These results underscore the association of body composition with axonal integrity and suggests that this relationship drives the association of NAA/Cr with physical fitness in young adults.

Obesity and the Brain: Another Brain-Body Versus Body-Brain Conundrum

Midlife obesity has been associated with poor cognitive functioning in older age, but the bidirectional pathways linking the brain and excessive adipose tissue require further research. In this issue of Psychosomatic Medicine, two investigations address the brain responses to food-related cues and psychological stressors relevant to obesity. Moazzami and colleagues document the relationship between abdominal obesity and brain responses to stress among patients with coronary artery disease and find that stress-related brain activity plays a potentially important role in the link between psychological distress, food cravings, and eating patterns relevant to obesity. Donofry and colleagues compare food cue-evoked functional connectivity in adults with obesity and report that brain areas involved in impaired self-regulation and reward processing may increase the risk of obesity by influencing decisions regarding diet and exercise. In this editorial, these findings are discussed in the context of brain-obesity interactions and the need for personalized multidisciplinary interventions for obesity. It is possible that functional magnetic resonance imaging and other indices of brain functioning will be useful in tailoring interventions that target weight reduction and/or cognitive functioning and monitoring treatment progress.

Prediction of disease-related metabolites using bi-random walks

Metabolites play a significant role in various complex human disease. The exploration of the relationship between metabolites and diseases can help us to better understand the underlying pathogenesis. Several network-based methods have been used to predict the association between metabolite and disease. However, some methods ignored hierarchical differences in disease network and failed to work in the absence of known metabolite-disease associations. This paper presents a bi-random walks based method for disease-related metabolites prediction, called MDBIRW. First of all, we reconstruct the disease similarity network and metabolite functional similarity network by integrating Gaussian Interaction Profile (GIP) kernel similarity of diseases and GIP kernel similarity of metabolites, respectively. Then, the bi-random walks algorithm is executed on the reconstructed disease similarity network and metabolite functional similarity network to predict potential disease-metabolite associations. At last, MDBIRW achieves reliable performance in leave-one-out cross validation (AUC of 0.910) and 5-fold cross validation (AUC of 0.924). The experimental results show that our method outperforms other existing methods for predicting disease-related metabolites.

Rapid metabolic shifts occur during the transition between hunger and satiety in Drosophila melanogaster

Metabolites are active controllers of cellular physiology, but their role in complex behaviors is less clear. Here we report metabolic changes that occur during the transition between hunger and satiety in Drosophila melanogaster. To analyze these data in the context of fruit fly metabolic networks, we developed Flyscape, an open-access tool. We show that in response to eating, metabolic profiles change in quick, but distinct ways in the heads and bodies. Consumption of a high sugar diet dulls the metabolic and behavioral differences between the fasted and fed state, and reshapes the way nutrients are utilized upon eating. Specifically, we found that high dietary sugar increases TCA cycle activity, alters neurochemicals, and depletes 1-carbon metabolism and brain health metabolites N-acetyl-aspartate and kynurenine. Together, our work identifies the metabolic transitions that occur during hunger and satiation, and provides a platform to study the role of metabolites and diet in complex behavior.

The relationship between metabolomic and behavioral changes is not well understood. Here, the authors analyze metabolome changes in D. melanogaster heads and bodies during hunger and satiety, and develop the Flyscape tool to visualize the resulting metabolic networks and integrate them with other omics data.

Effects of a long-term lifestyle intervention on metabolically healthy women with obesity: Metabolite profiles according to weight loss response

BACKGROUND & AIMS

The benefits of weight loss in subjects with metabolically healthy obesity (MHO) are still a matter of controversy. We aimed to identify metabolic fingerprints and their associated pathways that discriminate women with MHO with high or low weight loss response after a lifestyle intervention, based on a hypocaloric Mediterranean diet (MedDiet) and physical activity.

METHODS

A UPLC-Q-Exactive-MS/MS metabolomics workflow was applied to plasma samples from 27 women with MHO before and after 12 months of a hypocaloric weight loss intervention with a MedDiet and increased physical activity. The subjects were stratified into two age-matched groups according to weight loss: <10% (low weight loss group, LWL) and >10% (high weight loss group, HWL). Random forest analysis was performed to identify metabolites discriminating between the LWL and the HWL as well as within-status effects. Modulated pathways and associations between metabolites and anthropometric and biochemical variables were also investigated.

RESULTS

Thirteen metabolites discriminated between the LWL and the HWL, including 1,5-anhydroglucitol, carotenediol, 3-(4-hydroxyphenyl)lactic acid, N-acetylaspartate and several lipid species (steroids, a plasmalogen, sphingomyelins, a bile acid and long-chain acylcarnitines). 1,5-anhydroglucitol, 3-(4-hydroxyphenyl)lactic acid and sphingomyelins were positively associated with weight variables whereas N-acetylaspartate and the plasmalogen correlated negatively with them. Changes in very long-chain acylcarnitines and hydroxyphenyllactic levels were observed in the HWL and positively correlated with fasting glucose, and changes in levels of the plasmalogen negatively correlated with insulin resistance. Additionally, the cholesterol profile was positively associated with changes in acid hydroxyphenyllactic, sphingolipids and 1,5-AG.

CONCLUSIONS

Higher weight loss after a hypocaloric MedDiet and increased physical activity for 12 months is associated with changes in the plasma metabolome in women with MHO. These findings are associated with changes in biochemical variables and may suggest an improvement of the cardiometabolic risk profile in those patients that lose greater weight. Further studies are needed to investigate whether the response of those subjects with MHO to this intervention differs from those with unhealthy obesity.

Phenotypic heterogeneity of obesity-related brain vulnerability: one-size interventions will not fit all

Intact memory and problem solving are key to functional independence and quality of life in older age. Considering the unprecedented demographic shift toward a greater number of older adults than children in the United States in the next few decades, it is critically important for older adults to maintain work productivity and functional independence for as long as possible. Implementing early interventions focused on modifiable risk factors for cognitive decline at midlife is a strategy with the highest chance of success at present, bearing in mind the current lack of dementia cures. We present a selective, narrative review of evidence linking nutrition, body composition, vascular health, and brain function in midlife to highlight the phenotypic heterogeneity of obesity-related brain vulnerability and to endorse the development of individually tailored lifestyle modification plans for primary prevention of cognitive decline.