Prebiotic diet changes neural correlates of food decision-making in overweight adults: a randomised controlled within-subject cross-over trial.

OBJECTIVE: Animal studies suggest that prebiotic, plant-derived nutrients could improve homoeostatic and hedonic brain functions through improvements in microbiome-gut-brain communication. However, little is known if these results are applicable to humans. Therefore, we tested the effects of high-dosed prebiotic fibre on reward-related food decision-making in a randomised controlled within-subject cross-over study and assayed potential microbial and metabolic markers. DESIGN: 59 overweight young adults (19 females, 18-42 years, body mass index 25-30 kg/m2) underwent functional task MRI before and after 14 days of supplementary intake of 30 g/day of inulin (prebiotics) and equicaloric placebo, respectively. Short chain fatty acids (SCFA), gastrointestinal hormones, glucose/lipid and inflammatory markers were assayed in fasting blood. Gut microbiota and SCFA were measured in stool. RESULTS: Compared with placebo, participants showed decreased brain activation towards high-caloric wanted food stimuli in the ventral tegmental area and right orbitofrontal cortex after prebiotics (preregistered, family wise error-corrected p <0.05). While fasting blood levels remained largely unchanged, 16S-rRNA sequencing showed significant shifts in the microbiome towards increased occurrence of, among others, SCFA-producing Bifidobacteriaceae, and changes in >60 predicted functional signalling pathways after prebiotic intake. Changes in brain activation correlated with changes in Actinobacteria microbial abundance and associated activity previously linked with SCFA production, such as ABC transporter metabolism. CONCLUSIONS: In this proof-of-concept study, a prebiotic intervention attenuated reward-related brain activation during food decision-making, paralleled by shifts in gut microbiota. TRIAL REGISTRATION NUMBER: NCT03829189.

The Obese Taste Bud study: Objectives and study design.

AIMS: Taste modifies eating behaviour, impacting body weight and potentially obesity development. The Obese Taste Bud (OTB) Study is a prospective cohort study launched in 2020 at the University of Leipzig Obesity Centre in cooperation with the HI-MAG Institute. OTB will test the hypothesis that taste cell homeostasis and taste perception are linked to obesity. Here, we provide the study design, data collection process and baseline characteristics. MATERIALS AND METHODS: Participants presenting overweight, obesity or normal weight undergo taste and smell tests, anthropometric, and taste bud density (TBD) assessment on Day 1. Information on physical and mental health, eating behaviour, physical activity, and dental hygiene are obtained, while biomaterial (saliva, tongue swap, blood) is collected in the fasted state. Further blood samples are taken during a glucose tolerance test. A stool sample is collected at home prior to Day 2, on which a taste bud biopsy follows dental examination. A subsample undergoes functional magnetic resonance imaging while exposed to eating-related cognitive tasks. Follow-up investigations after conventional weight loss interventions and bariatric surgery will be included. RESULTS: Initial results show that glycated haemoglobin levels and age are negatively associated with TBD, while an unfavourable metabolic profile, current dieting, and vegan diet are related to taste perception. Olfactory function negatively correlates with age and high-density lipoprotein cholesterol. CONCLUSION: Initial findings suggest that metabolic alterations are relevant for taste and smell function and TBD. By combining omics data from collected biomaterial with physiological, metabolic and psychological data related to taste perception and eating behaviour, the OTB study aims to strengthen our understanding of taste perception in obesity.

Alterations in rhythmic and non-rhythmic resting-state EEG activity and their link to cognition in older age.

While many structural and biochemical changes in the brain have previously been associated with older age, findings concerning functional properties of neuronal networks, as reflected in their electrophysiological signatures, remain rather controversial. These discrepancies might arise due to several reasons, including diverse factors determining general spectral slowing in the alpha frequency range as well as amplitude mixing between the rhythmic and non-rhythmic parameters. We used a large dataset (N = 1703, mean age 70) to comprehensively investigate age-related alterations in multiple EEG biomarkers taking into account rhythmic and non-rhythmic activity and their individual contributions to cognitive performance. While we found strong evidence for an individual alpha peak frequency (IAF) decline in older age, we did not observe a significant relationship between theta power and age while controlling for IAF. Not only did IAF decline with age, but it was also positively associated with interference resolution in a working memory task primarily in the right and left temporal lobes suggesting its functional role in information sampling. Critically, we did not detect a significant relationship between alpha power and age when controlling for the 1/f spectral slope, while the latter one showed age-related alterations. These findings thus suggest that the entanglement of IAF slowing and power in the theta frequency range, as well as 1/f slope and alpha power measures, might explain inconsistencies reported previously in the literature. Finally, despite the absence of age-related alterations, alpha power was negatively associated with the speed of processing in the right frontal lobe while 1/f slope showed no consistent relationship to cognitive performance. Our results thus demonstrate that multiple electrophysiological features, as well as their interplay, should be considered for the comprehensive assessment of association between age, neuronal activity, and cognitive performance.

Neurobiology of eating behavior, nutrition, and health.

Eating behavior and food-related decision making are among the most complex of the motivated behaviors, and understanding the neurobiology of eating behavior, and its developmental dynamics, is critical to advancing the nutritional sciences and public health. Recent advances from both human and animal studies are revealing that individual capacity to make health-promoting food decisions varies based on biological and physiological variation in the signaling pathways that regulate the homeostatic, hedonic, and executive functions; past developmental exposures and current life-stage; the food environment; and complications of chronic disease that reinforce the obese state. Eating rate drives increased calorie intake and represents an important opportunity to lower rates of food consumption and energy intake through product reformulation. Understanding human eating behaviors and nutrition in the context of neuroscience can strengthen the evidence base from which dietary guidelines are derived and can inform policies, practices, and educational programs in a way that increases the likelihood they are adopted and effective for reducing rates of obesity and other diet-related chronic disease.

Neurocognitive predictors of food memory in healthy adults - A preregistered analysis.

Memory processes have long been known to determine food choices (Rozin & Zellner, 1985) but recognition memory of food and its cognitive, homeostatic and neuroanatomical predictors are still largely understudied. 60 healthy, overweight, non-restrictive eating adults (20 females) took part in a food wanting and subsequent food recognition and lure discrimination task at four time points after a standardized breakfast shake. With advanced tractography of 3 T diffusion-weighted imaging data, we investigated the influence of the uncinate fasciculus' (UF) brain microstructure on the interplay of food wanting and memory processes. The analysis was preregistered in detail and conducted with Bayesian multilevel regression modeling. Target recognition (d') and lure discrimination (LDI) performance of food tended to be higher than of art images while single image food memory accuracy evidently dominated art memory. On this single item level, wanting enhanced recognition accuracy and caloric content enhanced food memory accuracy. The enhancement by reward anticipation was most pronounced during memory encoding. Subjective hunger level did not predict performance on the memory task. The microstructure of the UF did neither evidently affect memory performance outcomes nor moderate the wanting enhancement of the recognition accuracy. Interestingly, female participants outperformed males on the memory task, and individuals with stronger neuroticism showed poorer memory performance. We shed light on to date understudied processes in food decision-making: reward anticipation influenced recognition accuracy and food memory was enhanced by higher caloric content, both effects might shape food decisions. Our findings indicate that brain microstructure does not affect food decision processes in adult populations with overweight. We suggest extending investigation of this interplay to brain activity as well as to populations with eating behaviour disorders.

Differences in white matter hyperintensities in socioeconomically deprived groups: results of the population-based LIFE Adult Study.

OBJECTIVE: Previous studies have shown that socioeconomically deprived groups exhibit higher lesion load of the white matter (WM) in aging. The aim of this study was to (i) investigate to what extent education and income may contribute to differences in white matter hyperintensities (WMHs) and (ii) identify risk profiles related to a higher prevalence of age-associated WMH. DESIGN AND SETTING: Population-based adult study of the Leipzig Research Centre for Civilization Diseases (LIFE) in Leipzig, Germany. PARTICIPANTS: Dementia-free sample aged 40-80 years (n = 1,185) derived from the population registry. MEASUREMENTS: Information was obtained in standardized interviews. WMH (including the derived Fazekas scores) were assessed using automated segmentation of high-resolution T1-weighted anatomical and fluid-attenuated inversion recovery (FLAIR) MRI acquired at 3T. RESULTS: Despite a significant association between income and WMH in univariate analyses, results from adjusted models (age, gender, arterial hypertension, heart disease, and APOE e4 allele) indicated no association between income and WMH. Education was associated with Fazekas scores, but not with WMH and not after Bonferroni correction. Prevalence of some health-related risk factors was significantly higher among low-income/education groups. After combining risk factors in a factor analysis, results from adjusted models indicated significant associations between higher distress and more WMH as well as between obesity and more deep WMH. CONCLUSIONS: Previously observed differences in WMH between socioeconomically deprived groups might stem from differences in health-related risk factors. These risk factors should be targeted in prevention programs tailored to socioeconomically deprived individuals.

[Sociodemographic and social correlates of self-reported resilience in old age-results from the population-based LIFE-Adult-Study]. / Soziodemografische und soziale Korrelate selbstberichteter Resilienz im Alter ­ Ergebnisse der populationsbasierten LIFE-Adult-Studie.

INTRODUCTION: Resilience describes good adaptation to adversity and is a significant factor for well-being in old age. Initial studies indicate a high relevance of social resources. So far, only few studies have investigated resilience patterns in the elderly population. Therefore, the present study aims to investigate sociodemographic and social correlates of resilience in a large population-based sample aged 65 years and older. METHODS: Analyses were conducted on n = 2410 people aged 65 years and older from the follow-up survey of the LIFE-Adult-Study. The survey included the variables resilience (Resilience Scale - RS-11), social support (ENRICHD Social Support Inventory - ESSI), and social network (Lubben Social Network Scale - LSNS-6). The association of sociodemographic and social variables with resilience was analyzed using multiple linear regression analysis. RESULTS: The age of 75 years and older was associated with lower resilience compared with the age of 65-74 years. Further, widowed marital status was related to higher resilience. Better social support and a larger social network were significantly associated with higher resilience. No association was found for gender and education. DISCUSSION: The results reveal sociodemographic correlates of resilience in the elderly population that can help identify at-risk groups with lower resilience. Social resources are significant in older age for resilient adaptation and represent a starting point for deriving preventive measures. Social inclusion of older people should be promoted to strengthen resilience in this population and provide favorable conditions for successful aging.

Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain.

Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with Layer-wise Relevance Propagation (LRP) to detect which brain features contribute to BA. Trained on magnetic resonance imaging (MRI) data of a population-based study (n = 2637, 18-82 years), our models estimated age accurately based on single and multiple modalities, regionally restricted and whole-brain images (mean absolute errors 3.37-3.86 years). We find that BA estimates capture ageing at both small and large-scale changes, revealing gross enlargements of ventricles and subarachnoid spaces, as well as white matter lesions, and atrophies that appear throughout the brain. Divergence from expected ageing reflected cardiovascular risk factors and accelerated ageing was more pronounced in the frontal lobe. Applying LRP, our study demonstrates how superior deep learning models detect brain-ageing in healthy and at-risk individuals throughout adulthood.

Social factors and the prevalence of social isolation in a population-based adult cohort.

PURPOSE: Social isolation has negative effects on physical and brain health across the lifespan. However, the prevalence of social isolation, specifically with regard to sociodemographic and socioeconomic factors, is not well known. METHODS: Database was the Leipzig population-based study of adults (LIFE-Adult Study, n = 10,000). The short form of the Lubben Social Network Scale (LSNS-6) was used to assess social isolation (cutoff < 12 points). Sampling weights were applied to account for differences in sampling fractions. RESULTS: Data were available for 9392 study participants; 51.6% were women, the mean age was 45.2 years (SD = 17.3). The prevalence of social isolation was 12.3% (95% CI 11.6-13.0) across ages 18-79 years. Social isolation was more prevalent in men (13.8%, 95% CI 12.8-14.8) compared to women (10.9%, 95% CI 10.0-11.8; [Formula: see text] (1) = 18.83, p < .001), and it showed an increase with increasing age from 5.4% (95% CI 4.7-6.0) in the youngest age group (18-39 years) to 21.7% (95% CI 19.5-24.0) in the oldest age group (70-79 years; [Formula: see text] (4) = 389.51, p < .001). Prevalence differed largely with regard to socioeconomic status (SES); showing lower prevalence in high SES (7.2%, 95% CI 6.0-8.4) and higher prevalence in low SES (18.6%, 95% CI 16.9-20.3; [Formula: see text] (2) = 115.78; p < .001). CONCLUSION: More than one in ten individuals in the adult population reported social isolation, and prevalence varied strongly with regard to sociodemographic and socioeconomic factors. Social isolation was particularly frequent in disadvantaged socioeconomic groups. From a public health perspective, effective prevention of and intervention against social isolation should be a desired target as social isolation leads to poor health. Countermeasures should especially take into account the socioeconomic determinants of social isolation, applying a life-course perspective.

Effects of bariatric surgery on functional connectivity of the reward and default mode network: A pre-registered analysis.

Obesity imposes serious health risks and involves alterations in resting-state functional connectivity of brain networks involved in eating behavior. Bariatric surgery is an effective treatment, but its effects on functional connectivity are still under debate. In this pre-registered study, we aimed to determine the effects of bariatric surgery on major resting-state brain networks (reward and default mode network) in a longitudinal controlled design. Thirty-three bariatric surgery patients and 15 obese waiting-list control patients underwent magnetic resonance imaging at baseline, after 6 and 12 months. We conducted a pre-registered whole-brain time-by-group interaction analysis, and a time-by-group interaction analysis on within-network connectivity. In exploratory analyses, we investigated the effects of weight loss and head motion. Bariatric surgery compared to waiting did not significantly affect functional connectivity of the reward network and the default mode network (FWE-corrected p > .05), neither whole-brain nor within-network. In exploratory analyses, surgery-related BMI decrease (FWE-corrected p = .041) and higher average head motion (FWE-corrected p = .021) resulted in significantly stronger connectivity of the reward network with medial posterior frontal regions. This pre-registered well-controlled study did not support a strong effect of bariatric surgery, compared to waiting, on major resting-state brain networks after 6 months. Exploratory analyses indicated that head motion might have confounded the effects. Data pooling and more rigorous control of within-scanner head motion during data acquisition are needed to substantiate effects of bariatric surgery on brain organization.

Higher BMI, but not obesity-related genetic polymorphisms, correlates with lower structural connectivity of the reward network in a population-based study.

BACKGROUND: Obesity is of complex origin, involving genetic and neurobehavioral factors. Genetic polymorphisms may increase the risk for developing obesity by modulating dopamine-dependent behaviors, such as reward processing. Yet, few studies have investigated the association of obesity, related genetic variants, and structural connectivity of the dopaminergic reward network. METHODS: We analyzed 347 participants (age range: 20-59 years, BMI range: 17-38 kg/m2) of the LIFE-Adult Study. Genotyping for the single nucleotid polymorphisms rs1558902 (FTO) and rs1800497 (near dopamine D2 receptor) was performed on a microarray. Structural connectivity of the reward network was derived from diffusion-weighted magnetic resonance imaging at 3 T using deterministic tractography of Freesurfer-derived regions of interest. Using graph metrics, we extracted summary measures of clustering coefficient and connectivity strength between frontal and striatal brain regions. We used linear models to test the association of BMI, risk alleles of both variants, and reward network connectivity. RESULTS: Higher BMI was significantly associated with lower connectivity strength for number of streamlines (ß = -0.0025, 95%-C.I.: [-0.004, -0.0008], p = 0.0042), and, to lesser degree, fractional anisotropy (ß = -0.0009, 95%-C.I. [-0.0016, -0.00008], p = 0.031), but not clustering coefficient. Strongest associations were found for left putamen, right accumbens, and right lateral orbitofrontal cortex. As expected, the polymorphism rs1558902 in FTO was associated with higher BMI (F = 6.9, p < 0.001). None of the genetic variants was associated with reward network structural connectivity. CONCLUSIONS: Here, we provide evidence that higher BMI correlates with lower reward network structural connectivity. This result is in line with previous findings of obesity-related decline in white matter microstructure. We did not observe an association of variants in FTO or near DRD2 receptor with reward network structural connectivity in this population-based cohort with a wide range of BMI and age. Future research should further investigate the link between genetics, obesity and fronto-striatal structural connectivity.

Global and Regional Development of the Human Cerebral Cortex: Molecular Architecture and Occupational Aptitudes.

We have carried out meta-analyses of genome-wide association studies (GWAS) (n = 23 784) of the first two principal components (PCs) that group together cortical regions with shared variance in their surface area. PC1 (global) captured variations of most regions, whereas PC2 (visual) was specific to the primary and secondary visual cortices. We identified a total of 18 (PC1) and 17 (PC2) independent loci, which were replicated in another 25 746 individuals. The loci of the global PC1 included those associated previously with intracranial volume and/or general cognitive function, such as MAPT and IGF2BP1. The loci of the visual PC2 included DAAM1, a key player in the planar-cell-polarity pathway. We then tested associations with occupational aptitudes and, as predicted, found that the global PC1 was associated with General Learning Ability, and the visual PC2 was associated with the Form Perception aptitude. These results suggest that interindividual variations in global and regional development of the human cerebral cortex (and its molecular architecture) cascade-albeit in a very limited manner-to behaviors as complex as the choice of one's occupation.

Weight loss reduces head motion: Revisiting a major confound in neuroimaging.

Head motion during magnetic resonance imaging (MRI) induces image artifacts that affect virtually every brain measure. In parallel, cross-sectional observations indicate a correlation of head motion with age, psychiatric disease status and obesity, raising the possibility of a systematic artifact-induced bias in neuroimaging outcomes in these conditions, due to the differences in head motion. Yet, a causal link between obesity and head motion has not been tested in an experimental design. Here, we show that a change in body mass index (BMI) (i.e., weight loss after bariatric surgery) systematically decreases head motion during MRI. In this setting, reduced imaging artifacts due to lower head motion might result in biased estimates of neural differences induced by changes in BMI. Overall, our finding urges the need to rigorously control for head motion during MRI to enable valid results of neuroimaging outcomes in populations that differ in head motion due to obesity or other conditions.

Visceral obesity relates to deep white matter hyperintensities via inflammation.

OBJECTIVE: White matter hyperintensities (WMHs) are linked to vascular risk factors and increase the risk of cognitive decline, dementia, and stroke. We here aimed to determine whether obesity contributes to regional WMHs using a whole-brain approach in a well-characterized population-based cohort. METHODS: Waist-to-hip ratio (WHR), body mass index (BMI), systolic/diastolic blood pressure, hypertension, diabetes and smoking status, blood glucose and inflammatory markers, as well as distribution of WMH were assessed in 1,825 participants of the LIFE-adult study (age, 20-82 years; BMI, 18.4-55.4 kg/m2 ) using high-resolution 3-Tesla magnetic resonance imaging. Voxel-wise analyses tested if obesity predicts regional probability of WMH. Additionally, mediation effects of high-sensitive C-reactive protein and interleukin-6 (IL6) measured in blood were related to obesity and WMH using linear regression and structural equation models. RESULTS: WHR related to higher WMH probability predominantly in the deep white matter, even after adjusting for effects of age, sex, and systolic blood pressure (mean ß = 0.0043 [0.0008 SE], 95% confidence interval, [0.00427, 0.0043]; threshold-free cluster enhancement, family-wise error-corrected p < 0.05). Conversely, higher systolic blood pressure was associated with WMH in periventricular white matter regions. Mediation analyses indicated that both higher WHR and higher BMI contributed to increased deep-to-periventricular WMH ratio through elevated IL6. INTERPRETATION: Our results indicate an increased WMH burden selectively in the deep white matter in obese subjects with high visceral fat accumulation, independent of common obesity comorbidities such as hypertension. Mediation analyses proposed that visceral obesity contributes to deep white matter lesions through increases in proinflammatory cytokines, suggesting a pathomechanistic link. Longitudinal studies need to confirm this hypothesis. ANN NEUROL 2019;85:194-203.

Neuroanatomical correlates of food addiction symptoms and body mass index in the general population.

The food addiction model suggests neurobiological similarities between substance-related and addictive disorders and obesity. While structural brain differences have been consistently reported in these conditions, little is known about the neuroanatomical correlates of food addiction. We therefore aimed to determine whether symptoms of food addiction related to body mass index (BMI), personality, and brain structure in a large population-based sample. Participants of the LIFE-Adult study (n = 625; 20-59 years old, 45% women) answered the Yale Food Addiction Scale (YFAS) and further personality measures, underwent anthropometric assessments and high-resolution 3T-neuroimaging. A higher YFAS symptom score correlated with higher BMI, eating behavior traits, neuroticism, and stress. Higher BMI predicted significantly lower thickness of (pre)frontal, temporal and occipital cortex and increased volume of left nucleus accumbens. In a whole-brain analysis, YFAS symptom score was not associated with significant differences in cortical thickness or subcortical gray matter volumes. A hypothesis-driven Bayes factor analysis suggested a small, additional contribution of YFAS symptom score to lower right lateral orbitofrontal cortex thickness over the effect of BMI. Our study indicates that symptoms of food addiction do not account for the major part of the structural brain differences associated with BMI in the general population. Yet, symptoms of food addiction might explain additional variance in orbitofrontal cortex, a hub area of the reward network. Longitudinal studies implementing both anatomical and functional MRI could further disentangle the neural mechanisms of addictive eating behaviors.

Using resting-state fMRI to assess the effect of aerobic exercise on functional connectivity of the DLPFC in older overweight adults.

Cardiovascular fitness is thought to exert beneficial effects on brain function and might delay the onset of cognitive decline. Empirical evidence of exercise-induced cognitive enhancement, however, has not been conclusive, possibly due to short intervention times in clinical trials. Resting-state functional connectivity (RSFC) has been proposed asan early indicator for intervention-induced changes. Here, we conducted a study in which healthy older overweight subjects took either part in a moderate aerobic exercise program over 6months (AE group; n=11) or control condition of non-aerobic stretching and toning (NAE group; n=18). While cognitive and gray matter volume changes were rather small (i.e., appeared only in certain sub-scores without Bonferroni correction for multiple comparisons or using small volume correction), we found significantly increased RSFC after training between dorsolateral prefrontal cortex and superior parietal gyrus/precuneus in the AE compared to the NAE group. This intervention study demonstrates an exercise-induced modulation of RSFC between key structures of the executive control and default mode networks, which might mediate an interaction between task-positive and task-negative brain activation required for task switching. Results further emphasize the value of RSFC asa sensitive biomarker for detecting early intervention-related cognitive improvements in clinical trials.

Effects of resveratrol on memory performance, hippocampus connectivity and microstructure in older adults - A randomized controlled trial.

INTRODUCTION: The polyphenol resveratrol has been suggested to exert beneficial effects on memory and the aging hippocampus due to calorie-restriction mimicking effects. However, the evidence based on human interventional studies is scarce. We therefore aimed to determine the effects of resveratrol on memory performance, and to identify potential underlying mechanisms using a broad array of blood-based biomarkers as well as hippocampus connectivity and microstructure assessed with ultra-high field magnetic resonance imaging (UHF-MRI). METHODS: In this double-blind, randomized controlled trial, 60 elderly participants (60-79 years) with a wide body-mass index (BMI) range of 21-37 kg/m2 were randomized to receive either resveratrol (200 mg/day) or placebo for 26 weeks (registered at ClinicalTrials.gov: NCT02621554). Baseline and follow-up assessments included the California Verbal Learning Task (CVLT, main outcome), the ModBent task, anthropometry, markers of glucose and lipid metabolism, inflammation and neurotrophins derived from fasting blood, multimodal neuroimaging at 3 and 7 T, and questionnaires to assess confounding factors. RESULTS: Multivariate repeated-measures ANOVA did not detect significant time by group effects for CVLT performance. There was a trend for preserved pattern recognition memory after resveratrol, while performance decreased in the placebo group (n.s., p = 0.07). Further exploratory analyses showed increases in both groups over time in body fat, cholesterol, fasting glucose, interleukin 6, high sensitive C-reactive protein, tumor necrosis factor alpha and in mean diffusivity of the subiculum and presubiculum, as well as decreases in physical activity, brain-derived neurotrophic factor and insulin-like growth factor 1 at follow-up, which were partly more pronounced after resveratrol. DISCUSSION: This interventional study failed to show significant improvements in verbal memory after 6 months of resveratrol in healthy elderly with a wide BMI range. A non-significant trend emerged for positive effects on pattern recognition memory, while possible confounding effects of unfavorable changes in lifestyle behavior, neurotrophins and inflammatory markers occurred. Our findings also indicate the feasibility to detect (un)healthy aging-related changes in measures of hippocampus microstructure after 6 months using 7T diffusion MRI. More studies incorporating a longer duration and larger sample size are needed to determine if resveratrol enhances memory performance in healthy older adults.

White matter microstructural variability mediates the relation between obesity and cognition in healthy adults.

Obesity has been linked with structural and functional brain changes. However, the impact of obesity on brain and cognition in aging remains debatable, especially for white matter. We therefore aimed to determine the effects of obesity on white matter microstructure and potential implications for cognition in a well-characterized large cohort of healthy adults. In total, 1255 participants (50% females, 19-80 years, BMI 16.8-50.2 kg/m2) with diffusion-weighted magnetic resonance imaging at 3T were analysed. Tract-based spatial statistics (TBSS) probed whether body mass index (BMI) and waist-to-hip ratio (WHR) were related to fractional anisotropy (FA). We conducted partial correlations and mediation analyses to explore whether obesity or regional FA were related to cognitive performance. Analyses were adjusted for demographic, genetic, and obesity-associated confounders. Results showed that higher BMI and higher WHR were associated with lower FA in multiple white matter tracts (p < 0.05, FWE-corrected). Mediation analyses provided evidence for indirect negative effects of higher BMI and higher WHR on executive functions and processing speed through lower FA in fiber tracts connecting (pre)frontal, visual, and associative areas (indirect paths, |ß| ≥ 0.01; 99% |CI| > 0). This large cross-sectional study showed that obesity is correlated with lower FA in multiple white matter tracts in otherwise healthy adults, independent of confounders. Moreover, although effect sizes were small, mediation results indicated that visceral obesity was linked to poorer executive functions and lower processing speed through lower FA in callosal and associative fiber tracts. Longitudinal studies are needed to support this hypothesis.

Social Network Types in Old Age and Incident Dementia.

Lack of social support has shown to be a major risk factor for poor health, mortality, and dementia. We analyzed what factors drive the likelihood of having restricted social networks and to what extent those factors then influence the risk of developing dementia. Our results from the Leipzig Longitudinal Study of the Aged (LEILA75+) indicate that older age (odds ratio [OR]: 1.04) and living with other people (OR: 2.12) was associated with a greater likelihood of having a restricted social network. A better cognitive status (OR: 0.84) was associated with a smaller likelihood of having a restricted social network. The risk of developing dementia over the follow-up period was significantly higher among individuals with restricted (hazard ratio: 2.11) than with integrated social networks. Our findings suggest that integrating elderly individuals in the wider community is a crucial indicator for dementia risk.

Caloric Restriction in Older Adults-Differential Effects of Weight Loss and Reduced Weight on Brain Structure and Function.

Dietary modifications such as caloric restriction (CR) have been suggested as a means to improve memory and prevent age-related decline. However, it is unclear whether those effects remain stable over time or are related specifically to negative energy balance during the weight loss phase of CR. Using a randomized interventional design, we investigated changes in recognition memory and neural correlates in postmenopausal obese women (n = 19): 1) after intense weight loss in the course of a 12-week low-caloric diet (reduced body weight and negative energy balance) and 2) after having sustained the reduced weight over 4 more weeks (reduced body weight, but energy balance equilibrium). Participants were contrasted to a control group (n = 18) instructed not to change dietary habits. In the CR group, we found improved recognition memory, paralleled by increased gray matter volume in inferior frontal gyrus and hippocampus, and augmented hippocampal resting-state functional connectivity to parietal areas. Moreover, effects were specific for transient negative energy balance and could not be detected after subsequent weight maintenance. Our data demonstrate for the first time in humans that beneficial effects of CR on brain structure and function are due to weight loss rather than an overall reduced weight.