Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

Effect of weight loss on knee joint synovitis over 48 months and mediation by subcutaneous fat around the knee: data from the Osteoarthritis Initiative.

BACKGROUND: Obesity influences the development of osteoarthritis via low-grade inflammation. Progression of local inflammation (= synovitis) increased with weight gain in overweight and obese women compared to stable weight. Synovitis could be associated with subcutaneous fat (SCF) around the knee. Purpose of the study was to investigate the effect of weight loss on synovitis progression and to assess whether SCF around the knee mediates the relationship between weight loss and synovitis progression. METHODS: We included 234 overweight and obese participants (body mass index [BMI] ≥ 25 kg/m2) from the Osteoarthritis Initiative (OAI) with > 10% weight loss (n = 117) or stable overweight (< ± 3% change, n = 117) over 48 months matched for age and sex. In magnetic resonance imaging (MRI) at baseline and 48 months, effusion-synovitis and Hoffa-synovitis using the MRI Osteoarthritis Knee Score (MOAKS) and average joint-adjacent SCF (ajSCF) were assessed. Odds-ratios (ORs) for synovitis progression over 48 months (≥ 1 score increase) were calculated in logistic regression models adjusting for age, sex, baseline BMI, Physical Activity Scale for the Elderly (PASE), and baseline SCF measurements. Mediation of the effect of weight loss on synovitis progression by local SCF change was assessed. RESULTS: Odds for effusion-synovitis progression decreased with weight loss and ajSCF decrease (odds ratio [OR] = 0.61 and 0.56 per standard deviation [SD] change, 95% confidence interval [CI] 0.44, 0.83 and 0.40, 0.79, p = 0.002 and 0.001, respectively), whereas odds for Hoffa-synovitis progression increased with weight loss and ajSCF decrease (OR = 1.47 and 1.48, CI 1.05, 2.04 and 1.02, 2.13, p = 0.024 and 0.038, respectively). AjSCF decrease mediated 39% of the effect of weight loss on effusion-synovitis progression. CONCLUSIONS: Effusion-synovitis progression was slowed by weight loss and decrease in local subcutaneous fat. Hoffa-synovitis characterized by fluid in the infrapatellar fat pad increased at the same time, suggesting a decreasing fat pad rather than active synovitis. Decrease in local subcutaneous fat partially mediated the systemic effect of weight loss on synovitis.

Velocity-selective arterial spin labeling perfusion measurements in 2nd trimester human placenta with varying BMI.

INTRODUCTION: Proper placental development is crucial to fetal health but is challenging to functionally assess non-invasively and is thus poorly characterized in populations. Body mass index (BMI) has been linked with adverse outcomes, but the causative mechanism is uncertain. Velocity-selective arterial spin labeling (VS-ASL) MRI provides a method to non-invasively measure placental perfusion with robustness to confounding transit time delays. In this study, we report on the measurement of perfusion in the human placenta in early pregnancy using velocity-selective arterial spin labeling (VS-ASL) MRI, comparing non-obese and obese participants. METHODS: Participants (N = 97) undergoing routine prenatal care were recruited and imaged with structural and VS-ASL perfusion MRI at 15 and 21 weeks gestation. Resulting perfusion images were analyzed with respect to obesity based on BMI, gestational age, and the presence of adverse outcomes. RESULTS: At 15 weeks gestation BMI was not associated with placental perfusion or perfusion heterogeneity. However, at 21 weeks gestation BMI was associated with higher placental perfusion (p < 0.01) and a decrease in perfusion heterogeneity (p < 0.05). In alignment with past studies, perfusion values were also higher at 21 weeks compared to 15 weeks gestation. In a small cohort of participants with adverse outcomes, at 21 weeks lower perfusion was observed compared to participants with uncomplicated pregnancies. DISCUSSION: These results suggest low placental perfusion in the early second trimester may not be the culpable factor driving associations of obesity with adverse outcomes.

Correlation between magnetic resonance imaging proton density fat fraction (MRI-PDFF) and liver biopsy to assess hepatic steatosis in obesity.

Obesity is highly associated with Non-alcoholic fatty liver disease (NAFLD) and increased risk of liver cirrhosis and liver cancer-related death. We determined the diagnostic performance of the complex-based chemical shift technique MRI-PDFF for quantifying liver fat and its correlation with histopathologic findings in an obese population within 24 h before bariatric surgery. This was a prospective, cross-sectional, Institutional Review Board-approved study of PDFF-MRI of the liver and MRI-DIXON image volume before bariatric surgery. Liver tissues were obtained during bariatric surgery. The prevalence of NAFLD in the investigated cohort was as high as 94%. Histologic hepatic steatosis grades 0, 1, 2, and 3 were observed in 3 (6%), 25 (50%), 14 (28%), and 8 (16%) of 50 obese patients, respectively. The mean percentages of MRI-PDFF from the anterior and posterior right hepatic lobe and left lobe vs. isolate left hepatic lobe were 15.6% (standard deviation [SD], 9.28%) vs. 16.29% (SD, 9.25%). There was a strong correlation between the percentage of steatotic hepatocytes and MRI-PDFF in the left hepatic lobe (r = 0.82, p < 0.001) and the mean value (r = 0.78, p < 0.001). There was a strong correlation between MRI-derived subcutaneous adipose tissue volume and total body fat mass by dual-energy X-ray absorptiometry, especially at the L2-3 and L4 level (r = 0.85, p < 0.001). MRI-PDFF showed good performance in assessing hepatic steatosis and was an excellent noninvasive technique for monitoring hepatic steatosis in an obese population.

White adipose tissue distribution and amount are associated with increased white matter connectivity.

Obesity represents a significant public health concern and is linked to various comorbidities and cognitive impairments. Previous research indicates that elevated body mass index (BMI) is associated with structural changes in white matter (WM). However, a deeper characterization of body composition is required, especially considering the links between abdominal obesity and metabolic dysfunction. This study aims to enhance our understanding of the relationship between obesity and WM connectivity by directly assessing the amount and distribution of fat tissue. Whole-body magnetic resonance imaging (MRI) was employed to evaluate total adipose tissue (TAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT), while MR liver spectroscopy measured liver fat content in 63 normal-weight, overweight, and obese males. WM connectivity was quantified using microstructure-informed tractography. Connectome-based predictive modeling was used to predict body composition metrics based on WM connectomes. Our analysis revealed a positive dependency between BMI, TAT, SAT, and WM connectivity in brain regions involved in reward processing and appetite regulation, such as the insula, nucleus accumbens, and orbitofrontal cortex. Increased connectivity was also observed in cognitive control and inhibition networks, including the middle frontal gyrus and anterior cingulate cortex. No significant associations were found between WM connectivity and VAT or liver fat. Our findings suggest that altered neural communication between these brain regions may affect cognitive processes, emotional regulation, and reward perception in individuals with obesity, potentially contributing to weight gain. While our study did not identify a link between WM connectivity and VAT or liver fat, further investigation of the role of various fat depots and metabolic factors in brain networks is required to advance obesity prevention and treatment approaches.

Obesity is associated with alterations in anatomical connectivity of frontal-corpus callosum.

Obesity has been linked to abnormal frontal function, including the white matter fibers of anterior portion of the corpus callosum, which is crucial for information exchange within frontal cortex. However, alterations in white matter anatomical connectivity between corpus callosum and cortical regions in patients with obesity have not yet been investigated. Thus, we enrolled 72 obese and 60 age-/gender-matched normal weight participants who underwent clinical measurements and diffusion tensor imaging. Probabilistic tractography with connectivity-based classification was performed to segment the corpus callosum and quantify white matter anatomical connectivity between subregions of corpus callosum and cortical regions, and associations between corpus callosum-cortex white matter anatomical connectivity and clinical behaviors were also assessed. Relative to normal weight individuals, individuals with obesity exhibited significantly greater white matter anatomical connectivity of corpus callosum-orbitofrontal cortex, which was positively correlated with body mass index and self-reported disinhibition of eating behavior, and lower white matter anatomical connectivity of corpus callosum-prefrontal cortex, which was significantly negatively correlated with craving for high-calorie food cues. The findings show that alterations in white matter anatomical connectivity between corpus callosum and frontal regions involved in reward and executive control are associated with abnormal eating behaviors.

Ultrasound-based measurement of central adiposity: Key considerations and guidelines.

Central adiposity, which is visceral and subcutaneous adiposity in the abdominal region, is a known risk factor for developing chronic cardiometabolic diseases. Central adiposity can be measured relatively inexpensively using ultrasound. Ultrasound has been shown to be precise and reliable, with measurement accuracy comparable to computed tomography and magnetic resonance. Despite the advantages conferred by ultrasound, widespread adoption has been hindered by lack of reliable standard operating procedures. To consolidate the literature and bring clarity to the use of ultrasound-derived measures of central adiposity, this review outlines (i) the [patho]physiological importance of central adiposity to cardiometabolic disease risk; (ii) an overview of the history and main technical aspects of ultrasound methodology; (iii) key measurement considerations, including transducer selection, subject preparation, image acquisition, image analysis, and operator training; and (iv) guidelines for standardized ultrasound protocols for measuring central adiposity.

Increased brain fractional perfusion in obesity using intravoxel incoherent motion (IVIM) MRI metrics.

OBJECTIVE: This research seeks to shed light on the associations between brain perfusion, cognitive function, and mental health in individuals with and without obesity. METHODS: In this study, we employed the noninvasive intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) technique to examine brain fractional perfusion (FP) in two groups: individuals with obesity (N = 72) and healthy controls (N = 66). Additionally, we investigated potential associations between FP, cognitive function, and depressive symptoms in the participants with and without obesity. Finally, artificial intelligence algorithms (Boruta analysis) were also used. RESULTS: Participants with obesity exhibited increased FP within dopaminergic brain circuits, particularly involving prefrontal cortex areas, anterior and posterior sections of the cingulate cortex, the right striatum, and the midbrain. Additionally, these individuals demonstrated lower working memory and higher depressive symptoms compared to the control group. Notably, higher FP in the inferior temporal and occipital cortices correlated with greater depressive symptoms, whereas increased FP in the right ventral caudate and the midbrain was associated with better working memory performance. A link between inflammatory and metabolic variables, with a particular emphasis on monocytes, and FP in obesity was also evidenced by Boruta analysis. CONCLUSIONS: Increased brain perfusion in individuals with obesity is associated with cognitive function and mental health through interaction with metabolic and inflammatory factors.

Adiposity influences on myocardial deformation: a cardiovascular magnetic resonance feature tracking study in people with overweight to obesity without established cardiovascular disease.

The objective of this study was to assess whether dietary-induced weight loss improves myocardial deformation in people with overweight to obesity without established cardiovascular disease applying cardiovascular magnetic resonance (CMR) with feature tracking (FT) based strain analysis. Ninety people with overweight to obesity without established cardiovascular disease (age 44.6 ± 9.3 years, body mass index (BMI) 32.6 ± 4 kg/m2) underwent CMR. We retrospectively quantified FT based strain and LA size and function at baseline and after a 6-month hypocaloric diet, with either low-carbohydrate or low-fat intake. The study cohort was compared to thirty-four healthy normal-weight controls (age 40.8 ± 16.0 years, BMI 22.5 ± 1.4 kg/m2). At baseline, the study cohort with overweight to obesity without established cardiovascular disease displayed significantly increased global circumferential strain (GCS), global radial strain (GRS) and LA size (all p < 0.0001 versus controls) but normal global longitudinal strain (GLS) and normal LA ejection fraction (all p > 0.05 versus controls). Dietary-induced weight loss led to a significant reduction in GCS, GRS and LA size irrespective of macronutrient composition (all p < 0.01). In a population with overweight to obesity without established cardiovascular disease subclinical myocardial changes can be detected applying CMR. After dietary-induced weight loss improvement of myocardial deformation could be shown. A potential clinical impact needs further studies.

Deep learning-based BMI inference from structural brain MRI reflects brain alterations following lifestyle intervention.

Obesity is associated with negative effects on the brain. We exploit Artificial Intelligence (AI) tools to explore whether differences in clinical measurements following lifestyle interventions in overweight population could be reflected in brain morphology. In the DIRECT-PLUS clinical trial, participants with criterion for metabolic syndrome underwent an 18-month lifestyle intervention. Structural brain MRIs were acquired before and after the intervention. We utilized an ensemble learning framework to predict Body-Mass Index (BMI) scores, which correspond to adiposity-related clinical measurements from brain MRIs. We revealed that patient-specific reduction in BMI predictions was associated with actual weight loss and was significantly higher in active diet groups compared to a control group. Moreover, explainable AI (XAI) maps highlighted brain regions contributing to BMI predictions that were distinct from regions associated with age prediction. Our DIRECT-PLUS analysis results imply that predicted BMI and its reduction are unique neural biomarkers for obesity-related brain modifications and weight loss.

Comparison between ultrasonography and computed tomography for measuring skeletal muscle mass in critically ill patients with different body mass index.

BACKGROUND & AIM: Among critical patients, there is an early onset of changes in both the quantity and quality of muscle mass. It is essential to find tools that promptly identify this muscle mass loss. The aim of this study was to compare the ultrasonography of the quadriceps femoris to the gold standard, thigh computed tomography (CT) for assessing the musculature of critically ill patients with different body mass index who have suffered traumatic brain injury. METHODS: This is a prospective validation study in an Intensive Care Unit (ICU) specialized in trauma care, located at a tertiary teaching hospital. Our study involved a convenience sample of patients. Sequential ultrasound and CT scans were performed at three distinct time intervals: upon admission, between 24 and 96 h' post-admission, and finally, between 96 and 168 h' post-admission. For all ultrasound measurements, we conducted simultaneous quadriceps CT measurements. The correlation between measurements obtained by ultrasound and computed tomography at three different times and in three BMI ranges was analyzed, in individuals with normal weight, overweight and obese. RESULTS: Results: We analyzed 252 images in 49 patients in time 1, 40 patients in time 2, and 37 in time 3 to compare the thickness quadriceps muscle using US and CT. Of these, 18 patients had a BMI ≤ 24.9 kg/m2 (normal weight), 18 patients from 25 to 29.9 kg/m2 (overweight), and 8 patients had a BMI ≥ 30 kg/m2 (obese). The mean age was 37 years, the majority (94%) were male and the main comorbidities were: hypertension 12%, diabetes 4% and 14% smoking. The results revealed minor discrepancies between measurements obtained through the two methods, these changes were not influenced by the body mass index, with these variations being practically insignificant in the context of clinical application. Thus, the correlation and concordance between the values obtained found a strong positive correlation with good limits of agreement. The Spearman's correlation coefficients obtained were r = 0.89, 0.91 and 0.88, p < 0.01 at T1, T2 and T3 respectively for normal weight, r = 0.91, 0.80 and 0.81, p < 0.01 at T1, T2 and T3 respectively for overweight and r = 0.89, 0.94 and 0.84, p < 0.01 at T1, T2 and T3 respectively for obesity. In addition to a positive correlation, we observed a high agreement between the methods. The Bland & Altman analysis at time 1 showed, respectively, the bias of 1.46, 2.03 and 0.76. At time 2, the bias was 0.42, 3.11 and 2.12. At time 3, the bias was 2.26, 3.38 and 2.11 mm. CONCLUSION: Our findings suggest that measure femoral quadriceps muscle thickness ultrasound-based exhibits a comparable performance to thigh CT. This conclusion stems from the excellent correlation and good agreement observed between ultrasound and CT, which is considered the gold standard for muscle assessment in critically ill patients. TRIAL REGISTRATION: This clinical trial is registered at REBEC https://ensaiosclinicos.gov.br/ identifier: RBR-2bzspnz. The protocol was approved, on July 30, 2019, by the Research Ethics Committee of the Hospital das Clínicas, Faculdade de Medicina de Ribeirão Preto - Trial Registration Number: 3,475,851.

Comparative study of abdominal CT enhancement in overweight and obese patients based on different scanning modes combined with different contrast medium concentrations.

PURPOSE: To compare image quality, iodine intake, and radiation dose in overweight and obese patients undergoing abdominal computed tomography (CT) enhancement using different scanning modes and contrast medium. METHODS: Ninety overweight and obese patients (25 kg/m2≤body mass index (BMI)< 30 kg/m2 and BMI≥30 kg/m2) who underwent abdominal CT-enhanced examinations were randomized into three groups (A, B, and C) of 30 each and scanned using gemstone spectral imaging (GSI) +320 mgI/ml, 100 kVp + 370 mgI/ml, and 120 kVp + 370 mgI/ml, respectively. Reconstruct monochromatic energy images of group A at 50-70 keV (5 keV interval). The iodine intake and radiation dose of each group were recorded and calculated. The CT values, contrast-to-noise ratios (CNRs), and subjective scores of each subgroup image in group A versus images in groups B and C were by using one-way analysis of variance or Kruskal-Wallis H test, and the optimal keV of group A was selected. RESULTS: The dual-phase CT values and CNRs of each part in group A were higher than or similar to those in groups B and C at 50-60 keV, and similar to or lower than those in groups B and C at 65 keV and 70 keV. The subjective scores of the dual-phase images in group A were lower than those of groups B and C at 50 keV and 55 keV, whereas no significant difference was seen at 60-70 keV. Compared to groups B and C, the iodine intake in group A decreased by 12.5% and 13.3%, respectively. The effective doses in groups A and B were 24.7% and 25.8% lower than those in group C, respectively. CONCLUSION: GSI +320 mgI/ml for abdominal CT-enhanced in overweight patients satisfies image quality while reducing iodine intake and radiation dose, and the optimal keV was 60 keV.

Development of a Non-Contact Sensor System for Converting 2D Images into 3D Body Data: A Deep Learning Approach to Monitor Obesity and Body Shape in Individuals in Their 20s and 30s.

This study demonstrates how to generate a three-dimensional (3D) body model through a small number of images and derive body values similar to the actual values using generated 3D body data. In this study, a 3D body model that can be used for body type diagnosis was developed using two full-body pictures of the front and side taken with a mobile phone. For data training, 400 3D body datasets (male: 200, female: 200) provided by Size Korea were used, and four models, i.e., 3D recurrent reconstruction neural network, point cloud generative adversarial network, skinned multi-person linear model, and pixel-aligned impact function for high-resolution 3D human digitization, were used. The models proposed in this study were analyzed and compared. A total of 10 men and women were analyzed, and their corresponding 3D models were verified by comparing 3D body data derived from 2D image inputs with those obtained using a body scanner. The model was verified through the difference between 3D data derived from the 2D image and those derived using an actual body scanner. Unlike the 3D generation models that could not be used to derive the body values in this study, the proposed model was successfully used to derive various body values, indicating that this model can be implemented to identify various body types and monitor obesity in the future.

Associations between adiposity and white matter hyperintensities: Cross-sectional and longitudinal analyses of 34,653 participants.

OBJECTIVES: White matter hyperintensities (WMH) increase the risk of stroke and cognitive impairment. This study aims to determine the cross-sectional and longitudinal associations between adiposity and WMH. METHODS: Participants were enrolled from the UK Biobank cohort. Associations of concurrent, past, and changes in overall and central adiposity with WMH were investigated by linear and nonlinear regression models. The association of longitudinal adiposity and WMH volume changes was determined by a linear mixed model. Mediation analysis investigated the potential mediating effect of blood pressure. RESULTS: In 34,653 participants with available adiposity measures and imaging data, the concurrent obese group had a 25.3% (ß [95% CI] = 0.253 [0.222-0.284]) higher WMH volume than the ideal weight group. Increment in all adiposity measures was associated with a higher WMH volume. Among them, waist circumference demonstrated the strongest effect (ß [95% CI] = 0.113 [0.101-0.125]). Past adiposity also demonstrated similar effects. Among the subset of 2664 participants with available WMH follow-up data, adiposity measures were predictive of WMH change. Regarding changes of adiposity, compared with ideal weight stable group, those who turned from ideal weight to overweight/obese had a 8.1% higher WMH volume (ß [95% CI] = 0.081 [0.039-0.123]), while participants who turned from overweight/obese to ideal weight demonstrated no significant WMH volume change. Blood pressure partly meditates the associations between adiposity and WMH. CONCLUSIONS: Both concurrent and past adiposity were associated with a higher WMH volume. The detrimental effects of adiposity on WMH occurred throughout midlife and in the elderly and may still exist after changes in obesity status.

Adults with metabolically healthy overweight or obesity present more brown adipose tissue and higher thermogenesis than their metabolically unhealthy counterparts.

BACKGROUND: There is a subset of individuals with overweight/obesity characterized by a lower risk of cardiometabolic complications, the so-called metabolically healthy overweight/obesity (MHOO) phenotype. Despite the relatively higher levels of subcutaneous adipose tissue and lower visceral adipose tissue observed in individuals with MHOO than individuals with metabolically unhealthy overweight/obesity (MUOO), little is known about the differences in brown adipose tissue (BAT). METHODS: This study included 53 young adults (28 women) with a body mass index (BMI) ≥25 kg/m2 which were classified as MHOO (n = 34) or MUOO (n = 19). BAT was assessed through a static 18F-FDG positron emission tomography/computed tomography scan after a 2-h personalized cooling protocol. Energy expenditure, skin temperature, and thermal perception were assessed during a standardized mixed meal test (3.5 h) and a 1-h personalized cold exposure. Body composition was assessed by dual-energy x-ray absorptiometry, energy intake was determined during an ad libitum meal test and dietary recalls, and physical activity levels were determined by a wrist-worn accelerometer. FINDINGS: Participants with MHOO presented higher BAT volume (+124%, P = 0.008), SUVmean (+63%, P = 0.001), and SUVpeak (+133%, P = 0.003) than MUOO, despite having similar BAT mean radiodensity (P = 0.354). In addition, individuals with MHOO exhibited marginally higher meal-induced thermogenesis (P = 0.096) and cold-induced thermogenesis (+158%, P = 0.050). Moreover, MHOO participants showed higher supraclavicular skin temperature than MUOO during the first hour of the postprandial period and during the cold exposure, while no statistically significant differences were observed in other skin temperature parameters. We observed no statistically significant differences between MHOO and MUOO in thermal perception, body composition, outdoor ambient temperature exposure, resting metabolic rate, energy intake, or physical activity levels. INTERPRETATION: Adults with MHOO present higher BAT volume and activity than MUOO. The higher meal- and cold-induced thermogenesis and cold-induced supraclavicular skin temperature are compatible with a higher BAT activity. Overall, these results suggest that BAT presence and activity might be linked to a healthier phenotype in young adults with overweight or obesity. FUNDING: See acknowledgments section.

Obesity surgery and neural correlates of human eating behaviour: A systematic review of functional MRI studies.

Changes in eating behaviour including reductions in appetite and food intake, and healthier food cue reactivity, reward, hedonics and potentially also preference, contribute to weight loss and its health benefits after obesity surgery. Functional magnetic resonance imaging (fMRI) has been increasingly used to interrogate the neural correlates of eating behaviour in obesity, including brain reward-cognitive systems, changes after obesity surgery, and links with alterations in the gut-hormone-brain axis. Neural responses to food cues can be measured by changes in blood oxygen level dependent (BOLD) signal in brain regions involved in reward processing, including caudate, putamen, nucleus accumbens, insula, amygdala, orbitofrontal cortex, and top-down inhibitory control, including dorsolateral prefrontal cortex (dlPFC). This systematic review aimed to examine: (i) results of human fMRI studies involving obesity surgery, (ii) important methodological differences in study design across studies, and (iii) correlations and associations of fMRI findings with clinical outcomes, other eating behaviour measures and mechanistic measures. Of 741 articles identified, 23 were eligible for inclusion: 16 (69.6%) longitudinal, two (8.7%) predictive, and five (21.7%) cross-sectional studies. Seventeen studies (77.3%) included patients having Roux-en-Y gastric bypass (RYGB) surgery, six (26.1%) vertical sleeve gastrectomy (VSG), and five (21.7%) laparoscopic adjustable gastric banding (LAGB). The majority of studies (86.0%) were identified as having a very low risk of bias, though only six (27.3%) were controlled interventional studies, with none including randomisation to surgical and control interventions. The remaining studies (14.0%) had a low risk of bias driven by their control groups not having an active treatment. After RYGB surgery, food cue reactivity often decreased or was unchanged in brain reward systems, and there were inconsistent findings as to whether reductions in food cue reactivity was greater for high-energy than low-energy foods. There was minimal evidence from studies of VSG and LAGB surgeries for changes in food cue reactivity in brain reward systems, though effects of VSG surgery on food cue reactivity in the dlPFC were more consistently found. There was consistent evidence for post-operative increases in satiety gut hormones glucagon-like-peptide 1 (GLP-1) and peptide YY (PYY) mediating reduced food cue reactivity after RYGB surgery, including two interventional studies. Methodological heterogeneity across studies, including nutritional state, nature of food cues, post-operative timing, lack of control groups for order effects and weight loss or dietary/psychological advice, and often small sample sizes, limited the conclusions that could be drawn, especially for correlational analyses with clinical outcomes, other eating behaviour measures and potential mediators. This systematic review provides a detailed data resource for those performing or analysing fMRI studies of obesity surgery and makes suggestions to help improve reporting and design of such studies, as well as future directions.

Hypothalamic subregion alterations in anorexia nervosa and obesity: Association with appetite-regulating hormone levels.

OBJECTIVE: Anorexia nervosa (AN) and obesity are weight-related disorders with imbalances in energy homeostasis that may be due to hormonal dysregulation. Given the importance of the hypothalamus in hormonal regulation, we aimed to identify morphometric alterations to hypothalamic subregions linked to these conditions and their connection to appetite-regulating hormones. METHODS: Structural magnetic resonance imaging (MRI) was obtained from 78 patients with AN, 27 individuals with obesity and 100 normal-weight healthy controls. Leptin, ghrelin, and insulin blood levels were measured in a subsample of each group. An automated segmentation method was used to segment the hypothalamus and its subregions. Volumes of the hypothalamus and its subregions were compared between groups, and correlational analysis was employed to assess the relationship between morphometric measurements and appetite-regulating hormone levels. RESULTS: While accounting for total brain volume, patients with AN displayed a smaller volume in the inferior-tubular subregion (ITS). Conversely, obesity was associated with a larger volume in the anterior-superior, ITS, posterior subregions (PS), and entire hypothalamus. There were no significant volumetric differences between AN subtypes. Leptin correlated positively with PS volume, whereas ghrelin correlated negatively with the whole hypothalamus volume in the entire cohort. However, appetite-regulating hormone levels did not mediate the effects of body mass index on volumetric measures. CONCLUSION: Our results indicate the importance of regional structural hypothalamic alterations in AN and obesity, extending beyond global changes to brain volume. Furthermore, these alterations may be linked to changes in hormonal appetite regulation. However, given the small sample size in our correlation analysis, further analyses in a larger sample size are warranted. PUBLIC SIGNIFICANCE: Using an automated segmentation method to investigate morphometric alterations of hypothalamic subregions in AN and obesity, this study provides valuable insights into the complex interplay between hypothalamic alterations, hormonal appetite regulation, and body weight, highlighting the need for further research to uncover underlying mechanisms.

Improving our understanding of the paradoxical protective effect of obesity on radiographic damage: a large magnetic resonance imaging-study in early arthritis.

OBJECTIVE: Obesity conveys a risk for RA development, while paradoxically, associating with less radiographic progression after RA diagnosis. Using MRI we can study this surprising association in detail from MRI-detected synovitis and osteitis to MRI-detected erosive progression, which precedes radiographic progression. Previous research suggested obesity associates with less osteitis and synovitis. We therefore aimed to (i) validate the previously suggested association between BMI and MRI-detected osteitis/synovitis; (ii) study whether this is specific for ACPA-positive or ACPA-negative RA or also present in other arthritides; (iii) study whether MRI-detected osteitis associates with MRI-detected erosive progression; and (iv) study whether obesity associates with MRI-detected erosive progression. METHODS: We studied 1029 early arthritis patients (454 RA, 575 other arthritides), consecutively included in Leiden Early Arthritis Clinic. At baseline patients underwent hand-and-foot MRI that were RAMRIS-scored, and 149 RA patients underwent follow-up MRIs. We studied associations between baseline BMI and MRI-detected osteitis/synovitis (using linear regression), and erosive progression (using Poisson mixed models). RESULTS: In RA, higher BMI associated with less osteitis at disease onset (ß = 0.94; 95% CI: 0.93, 0.96) but not with synovitis. Higher BMI associated with less osteitis in ACPA-positive RA (ß = 0.95; 95% CI: 0.93, 0.97), ACPA-negative RA (ß = 0.97; 95% CI: 0.95, 0.99) and other arthritides (ß = 0.98; 95% CI: 0.96, 0.99). Over 2 years, overweight and obesity associated with less MRI-detected erosive progression (P = 0.02 and 0.03, respectively). Osteitis also associated with erosive progression over 2 years (P < 0.001). CONCLUSIONS: High BMI relates to less osteitis at disease onset, which is not confined to RA. Within RA, high BMI and less osteitis associated with less MRI-detected erosive progression. This suggests that the protective effect of obesity on radiographic progression is exerted via a path of less osteitis and subsequently fewer MRI-detected erosions.

Association of Anthropometric and CT-Based Obesity Indices with Subclinical Atherosclerosis.

AIM: Few studies have compared the strength in the associations of anthropometric and computed tomography (CT)-based obesity indices with coronary artery calcification (CAC), aortic artery calcification (AoAC), and aortic valve calcification (AVC). METHODS: We assessed cross-sectcional associations of anthropometric and CT-based obesity indices with CAC, AoAC, and AVC. Anthropometric measures included body mass index (BMI), waist circumference, hip ircumference, waist-to-hip circumference ratio, and waist-to-height ratio in 931 men (mean age, 63.7 years) from a population-based cohort. CT images at the L4/5 level were obtained to calculate the areas of abdominal visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), total adipose tissue (TAT), VAT-to-SAT ratio (VSR), and VAT-to-TAT ratio (VTR). CAC, AoAC, and AVC were quantified using the Agatston score based on CT scanning. RESULTS: CAC, AVC, and AoAC were present in 348 (62.6%), 173 (18.6%), and 769 (82.6%) participants, respectively. In multivariable models adjusting for age, lifestyle factors, and CT types (electron beam CT and multidetector row CT), anthropometric and CT-based obesity indices were positively associated with CAC (p＜0.01). Conversely, VAT-to-SAT ratio and VAT-to-TAT ratio were positively associated with AoAC (p＜0.01). Any obesity indices were not associated with AVC. CONCLUSIONS: The strength of the associations of obesity indices with subclinical atherosclerosis varied according to the anatomically distinct atherosclerotic lesions, among men.