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.

From the reward network to whole-brain metrics: structural connectivity in adolescents and young adults according to body mass index and genetic risk of obesity.

BACKGROUND: Obesity is a multifactorial condition. Genetic variants, such as the fat mass and obesity related gene (FTO) polymorphism, may increase the vulnerability of developing obesity by disrupting dopamine signaling within the reward network. Yet, the association of obesity, genetic risk of obesity, and structural connectivity of the reward network in adolescents and young adults remains unexplored. We investigate, in adolescents and young adults, the structural connectivity differences in the reward network and at the whole-brain level according to body mass index (BMI) and the FTO rs9939609 polymorphism. METHODS: One hundred thirty-two adolescents and young adults (age range: [10, 21] years, BMI z-score range: [-1.76, 2.69]) were included. Genetic risk of obesity was determined by the presence of the FTO A allele. Whole-brain and reward network structural connectivity were analyzed using graph metrics. Hierarchical linear regression was applied to test the association between BMI-z, genetic risk of obesity, and structural connectivity. RESULTS: Higher BMI-z was associated with higher (B = 0.76, 95% CI = [0.30, 1.21], P = 0.0015) and lower (B = -0.003, 95% CI = [-0.006, -0.00005], P = 0.048) connectivity strength for fractional anisotropy at the whole-brain level and of the reward network, respectively. The FTO polymorphism was not associated with structural connectivity nor with BMI-z. CONCLUSIONS: We provide evidence that, in healthy adolescents and young adults, higher BMI-z is associated with higher connectivity at the whole-brain level and lower connectivity of the reward network. We did not find the FTO polymorphism to correlate with structural connectivity. Future longitudinal studies with larger sample sizes are needed to assess how genetic determinants of obesity change brain structural connectivity and behavior.

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.

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.

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.

Hemispheric asymmetries in resting-state EEG and fMRI are related to approach and avoidance behaviour, but not to eating behaviour or BMI.

Much of our behaviour is driven by two motivational dimensions-approach and avoidance. These have been related to frontal hemispheric asymmetries in clinical and resting-state EEG studies: Approach was linked to higher activity of the left relative to the right hemisphere, while avoidance was related to the opposite pattern. Increased approach behaviour, specifically towards unhealthy foods, is also observed in obesity and has been linked to asymmetry in the framework of the right-brain hypothesis of obesity. Here, we aimed to replicate previous EEG findings of hemispheric asymmetries for self-reported approach/avoidance behaviour and to relate them to eating behaviour. Further, we assessed whether resting fMRI hemispheric asymmetries can be detected and whether they are related to approach/avoidance, eating behaviour and BMI. We analysed three samples: Sample 1 (n = 117) containing EEG and fMRI data from lean participants, and Samples 2 (n = 89) and 3 (n = 152) containing fMRI data from lean, overweight and obese participants. In Sample 1, approach behaviour in women was related to EEG, but not to fMRI hemispheric asymmetries. In Sample 2, approach/avoidance behaviours were related to fMRI hemispheric asymmetries. Finally, hemispheric asymmetries were not related to either BMI or eating behaviour in any of the samples. Our study partly replicates previous EEG findings regarding hemispheric asymmetries and indicates that this relationship could also be captured using fMRI. Our findings suggest that eating behaviour and obesity are likely to be mediated by mechanisms not directly relating to frontal asymmetries in neuronal activation quantified with EEG and fMRI.

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.

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.

Predicting brain-age from multimodal imaging data captures cognitive impairment.

The disparity between the chronological age of an individual and their brain-age measured based on biological information has the potential to offer clinically relevant biomarkers of neurological syndromes that emerge late in the lifespan. While prior brain-age prediction studies have relied exclusively on either structural or functional brain data, here we investigate how multimodal brain-imaging data improves age prediction. Using cortical anatomy and whole-brain functional connectivity on a large adult lifespan sample (N=2354, age 19-82), we found that multimodal data improves brain-based age prediction, resulting in a mean absolute prediction error of 4.29 years. Furthermore, we found that the discrepancy between predicted age and chronological age captures cognitive impairment. Importantly, the brain-age measure was robust to confounding effects: head motion did not drive brain-based age prediction and our models generalized reasonably to an independent dataset acquired at a different site (N=475). Generalization performance was increased by training models on a larger and more heterogeneous dataset. The robustness of multimodal brain-age prediction to confounds, generalizability across sites, and sensitivity to clinically-relevant impairments, suggests promising future application to the early prediction of neurocognitive disorders.

Higher body mass index is associated with reduced posterior default mode connectivity in older adults.

Obesity is a complex neurobehavioral disorder that has been linked to changes in brain structure and function. However, the impact of obesity on functional connectivity and cognition in aging humans is largely unknown. Therefore, the association of body mass index (BMI), resting-state network connectivity, and cognitive performance in 712 healthy, well-characterized older adults of the Leipzig Research Center for Civilization Diseases (LIFE) cohort (60-80 years old, mean BMI 27.6 kg/m2 ± 4.2 SD, main sample: n = 521, replication sample: n = 191) was determined. Statistical analyses included a multivariate model selection approach followed by univariate analyses to adjust for possible confounders. Results showed that a higher BMI was significantly associated with lower default mode functional connectivity in the posterior cingulate cortex and precuneus. The effect remained stable after controlling for age, sex, head motion, registration quality, cardiovascular, and genetic factors as well as in replication analyses. Lower functional connectivity in BMI-associated areas correlated with worse executive function. In addition, higher BMI correlated with stronger head motion. Using 3T neuroimaging in a large cohort of healthy older adults, independent negative associations of obesity and functional connectivity in the posterior default mode network were observed. In addition, a subtle link between lower resting-state connectivity in BMI-associated regions and cognitive function was found. The findings might indicate that obesity is associated with patterns of decreased default mode connectivity similar to those seen in populations at risk for Alzheimer's disease. Hum Brain Mapp 38:3502-3515, 2017. © 2017 Wiley Periodicals, Inc.

Hypothalamic atrophy and structural covariance in amnestic mild cognitive impairment and Alzheimer's dementia.

BACKGROUND: Alzheimer's disease (AD) is characterized by progressive cognitive decline and specific brain atrophy patterns, primarily involving the medial temporal lobes. A number of studies have discussed hypothalamic involvement in AD with consecutive metabolic and/or autonomic disturbances yet only few studies have investigated hypothalamic atrophy in AD and its early stages in particular. METHODS: We applied semi-automated volumetry of the hypothalamus (HTH) in 3 T MRI in a sample N = 175 participants [age 74.9 ± 7.22; gender 85 m/90f; cognitively normal controls (CN; N = 56); amnestic mild cognitive impairment (MCI; N = 78); AD (N = 41)] from the Alzheimer's Disease Neuroimaging Initiative (ADNI). In addition, we used voxel-based morphometry (VBM), cortical thickness (CTH) analyses and source-based morphometry (SBM) derived networks of structural covariance to investigate brain structural covariance patterns of the HTH under consideration of diagnostic groups, ß-amyloid (AB) positivity and apolipoprotein E (APOE) ε4 status. RESULTS: Hypothalamic atrophy was observed in both early and advanced disease stages (i.e. hypothalamic volume CN > MCI > AD). VBM, CTH analysis and SBM revealed positive associations between hypothalamic volume (HV) and AD-vulnerable regions, largely corresponding to the Papez circuit and brain regions implicated in autonomic regulation, however, group differences regarding HTH structural covariance were not observed. Similar observations were made in carriers and non-carriers of the ε4 allele, yet more pronounced in ε4 carriers. Although not reaching significance, comparisons of AB positive vs. negative subjects indicated stronger HTH atrophy in biomarker positive participants. HV was not associated with body mass index or longitudinal weight change. CONCLUSIONS: Our findings support early structural changes of the HTH in AD. HV covaries with regional volumes of AD-vulnerable regions. This could point to secondary atrophy of the HTH following atrophy of the hippocampus and other structures of the Papez circuit in AD.

Glycemic control contributes to the neuroprotective effects of Mediterranean and green-Mediterranean diets on brain age: the DIRECT PLUS brain-magnetic resonance imaging randomized controlled trial.

BACKGROUND: We recently reported that Mediterranean (MED) and green-MED diets significantly attenuated age-related brain atrophy by ∼50% within 18 mo. OBJECTIVE: The objective of this study was to explore the contribution of specific diet-induced parameters to brain-volume deviation from chronologic age. METHODS: A post hoc analysis of the 18-mo DIRECT PLUS trial, where participants were randomly assigned to the following groups: 1) healthy dietary guidelines, 2) MED diet, or 3) green-MED diet, high in polyphenols, and low in red meat. Both MED groups consumed 28 g walnuts/d (+440 mg/d polyphenols). The green-MED group further consumed green tea (3-4 cups/d) and Mankai green shake (Wolffia globosa aquatic plant) (+800 mg/d polyphenols). We collected blood samples through the intervention and followed brain structure volumes by magnetic resonance imaging (MRI). We used hippocampal occupancy (HOC) score (hippocampal and inferior lateral-ventricle volumes ratio) as a neurodegeneration marker and brain-age proxy. We applied multivariate linear regression models. RESULTS: Of 284 participants [88% male; age = 51.1 y; body mass index = 31.2 kg/m2; hemoglobin A1c (HbA1c) = 5.48%; APOE-ε4 genotype = 15.7%], 224 completed the trial with eligible whole-brain MRIs. Individuals with higher HOC deviations (i.e., younger brain age) presented lower body weight [r = -0.204; 95% confidence interval (CI): -0.298, -0.101], waist circumference (r = -0.207; 95% CI: -0.310, -0.103), diastolic (r = -0.186; 95% CI: -0.304, -0.072), systolic blood pressure (r = -0.189; 95% CI: -0.308, -0.061), insulin (r = -0.099; 95% CI: -0.194, -0.004), and HbA1c (r = -0.164; 95% CI: -0.337, -0.006) levels. After 18 mo, greater changes in HOC deviations (i.e., brain-age decline attenuation) were independently associated with improved HbA1c (ß = -0.254; 95% CI: -0.392, -0.117), HOMA-IR (ß = -0.200; 95% CI: -0.346, -0.055), fasting glucose (ß = -0.155; 95% CI: -0.293, -0.016), and c-reactive protein (ß = -0.153; 95% CI: -0.296, -0.010). Improvement in diabetes status was associated with greater HOC deviation changes than either no change in diabetes status (0.010; 95% CI: 0.002, 0.019) or with an unfavorable change (0.012; 95% CI: 0.002, 0.023). A decline in HbA1c was further associated with greater deviation changes in the thalamus, caudate nucleus, and cerebellum (P < 0.05). Greater consumption of Mankai and green tea (green-MED diet components) were associated with greater HOC deviation changes beyond weight loss. CONCLUSIONS: Glycemic control contributes to the neuroprotective effects of the MED and green-MED diets on brain age. Polyphenols-rich diet components as Mankai and green tea may contribute to a more youthful brain age. This trial was registered at clinicaltrials.gov at clinicaltrials.gov as NCT03020186.

Genetic variants for head size share genes and pathways with cancer.

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

Changes in the superior longitudinal fasciculus and anterior thalamic radiation in the left brain are associated with developmental dyscalculia.

Developmental dyscalculia is a neurodevelopmental disorder specific to arithmetic learning even with normal intelligence and age-appropriate education. Difficulties often persist from childhood through adulthood lowering the individual's quality of life. However, the neural correlates of developmental dyscalculia are poorly understood. This study aimed to identify brain structural connectivity alterations in developmental dyscalculia. All participants were recruited from a large scale, non-referred population sample in a longitudinal design. We studied 10 children with developmental dyscalculia (11.3 ± 0.7 years) and 16 typically developing peers (11.2 ± 0.6 years) using diffusion-weighted magnetic resonance imaging. We assessed white matter microstructure with tract-based spatial statistics in regions-of-interest tracts that had previously been related to math ability in children. Then we used global probabilistic tractography for the first time to measure and compare tract length between developmental dyscalculia and typically developing groups. The high angular resolution diffusion-weighted magnetic resonance imaging and crossing-fiber probabilistic tractography allowed us to evaluate the length of the pathways compared to previous studies. The major findings of our study were reduced white matter coherence and shorter tract length of the left superior longitudinal/arcuate fasciculus and left anterior thalamic radiation in the developmental dyscalculia group. Furthermore, the lower white matter coherence and shorter pathways tended to be associated with the lower math performance. These results from the regional analyses indicate that learning, memory and language-related pathways in the left hemisphere might be related to developmental dyscalculia in children.