International Journal of Obesity

Background: 39M children worldwide are overweight or have obesity, accelerating risk for adult non-communicable diseases. Presently, interventions to prevent obesity have had limited success due to poor timing and lack of personalisation. Objective: We aimed to identify early-life predictors of childhood obesity (ChOB) that could aid targeting specific population subsets for obesity prevention interventional studies. Methods: Data were from the Raine Study Gen2 participants (n=1494). Anthropometric and genetic predictors evaluated included birthweight (BW), early-life BMI (1-3 years), and three polygenic scores (PGS) [two BW-PGSs (BW-PGS2016 and BW-PGS2019) and a ChOB-PGS], developed from BW and ChOB genome-wide-association-studies, respectively. Multivariate analyses were performed to investigate associations between predictors and child-BMI (5-, 8-, 10-years). Results: BW-PGS2019 associate with child-BMI at 5-years. BW-PGS2016 was not associated with child-BMI. Remaining predictors positively associate with child-BMI at 5-, 8- and 10-years (p<0.001). Early-life BMI, ChOB-PGS and BW accounted for up to 38.7%, 5.8% and 3.4% of the variability in child-BMI, respectively. Conclusions: Our data suggest early-life BMI is a better predictor of child-BMI than ChOB-PGS, and BW, accounting for up to ten-fold more variance in child-BMI. Future interventional studies to mitigate obesity could target early-life BMI as a marker to identify children at the highest risk.

BackgroundEthnic minorities and socioeconomically disadvantaged populations in the UK are at increased risk of obesity. We modelled longitudinal body mass index (BMI) trajectories through infancy, childhood, and adolescence to identify at-risk groups and modifiable risk factors. MethodsThis cohort sampled 10,350 White and South Asian children born in Leicestershire, 1985-1997. We included 5,571 participants with [&ge;]3 BMI measurements between 0-18 years collected from healthcare records, questionnaires, and study visits. We used Group-Based Trajectory Modelling of BMI, separately by sex and ethnicity, and combined. We identified at-risk groups and modifiable risk factors using multinomial logistic regression, with inverse probability weighting to reduce selection bias. ResultsWe identified similar five BMI trajectories across sex and ethnicity: stable normal BMI (47%); persistent low BMI (30%); early overweight resolving (8%); childhood onset obesity (4%); and adolescent onset overweight (11%). Childhood onset obesity deviated from stable normal BMI at 2-4 years of age, adolescent onset overweight at 4-6 years. South Asians were at higher risk of childhood onset obesity (aOR: 1.66 [95%CI 1.08-2.53]) and adolescent onset overweight (1.29 [0.98-1.71]) than Whites. Children from deprived backgrounds (1.66 [0.92-2.82], most vs least deprived quintile) and those with less educated parents (1.67 [1.08-2.63], compulsory vs higher education) were at increased risk of childhood onset obesity. Smoking during pregnancy (1.50 [0.88-2.54]) and absence of breastfeeding (1.56 [1.07-2.29]) increased risk of childhood onset obesity. Physical activity decreased risk of childhood onset obesity (0.64 [0.44-0.93], [&ge;]4 vs 0-3 hours/week) and adolescent onset overweight (0.75 [0.59-0.94]). ConclusionBMI trajectories diverge as early as age 2 years, revealing ethnic and social inequalities. Obesity strategies in the UK should intervene during critical windows in early life and prioritise South Asian children and those from socioeconomically deprived backgrounds.

ObjectiveBMI alone does not capture obesity-related health heterogeneity. The Edmonton Obesity Staging System (EOSS) grades obesity severity based on comorbidities and functional impairment, whereas the Lancet Commission Diagnostic Model for Obesity (DMO) distinguishes preclinical from clinical obesity based on organ dysfunction. We assessed whether both frameworks identify overlapping phenotypes and how they classify obesity severity. MethodsA modified EOSS and DMO were applied to the UK Biobank (N {approx} 411,000). Stage distributions, cross-classification, and the impact of combining BMI with fat distribution on obesity categorization were analyzed. ResultsAbout one quarter of participants were classified with obesity under both frameworks. Most were assigned to advanced stages, with high concordance for established disease. Differences were most pronounced in early stages: DMO captured a broader spectrum of mild/subclinical organ dysfunction, whereas EOSS emphasized established disease with prognostic relevance. Discrepancies reflected differences in operationalization of e.g. metabolic, cardiovascular, and mental health. Obesity thresholds influenced classification, with [~]50% reclassified when BMI was combined with different fat distribution parameters, highlighting sensitivity of early-stage assignment. ConclusionEOSS and DMO provide complementary perspectives on obesity severity. Integrating EOSSs prognostic granularity with DMOs multidimensional approach may improve risk stratification and identify individuals most suitable for intensive interventions. STUDY IMPORTANCEO_ST_ABSWhat is already known?C_ST_ABSO_LIBMI alone poorly reflects obesity-related health risk; comorbidities, organ dysfunction, and functional impairments are crucial for precise staging. C_LIO_LITwo major frameworks exist: EOSS focuses on prognostic severity, while DMO identifies early/preclinical obesity--but their agreement and clinical implications were unclear. C_LI What does this study add?O_LIDemonstrates that EOSS emphasizes established disease and prognostic severity, whereas DMO captures a broader spectrum of early or subclinical organ dysfunction, revealing distinct phenotypes within the same BMI-defined population. C_LIO_LIHighlights that combining BMI with anthropometric measures can reclassify up to [~]50% of individuals, illustrating the sensitivity of early-stage assignment to diagnostic thresholds. C_LI How might these results change the direction of research or the focus of clinical practice?O_LIIntegrating EOSSs prognostic detail with DMOs broad, multidimensional approach enables targeted intervention, helping clinicians prioritize patients for intensive obesity management or treatment. C_LIO_LIProvides evidence for harmonizing obesity classification beyond BMI, emphasizing the need for multidimensional assessment in both research cohorts and routine clinical practice. C_LI

BackgroundThe timing of energy intake could be important in the development of obesity. However, most observational evidence stems from adults, anthropometric defined obesity outcomes, single meal timing phenotyping, and traditional regression modeling. ObjectiveWe aimed to describe meal timing patterns in adolescents and determine if they associated with fat mass by modeling the median and all other percentiles of the frequency distribution. MethodsWe analyzed data from the Sleep and Growth Study 2 (S-Grow2, N=286, 12-13y). Participants completed 3-day 24-hour dietary recalls and time stamped eating occasions were used to define 8 meal timing traits, with aide from self-reported wake and bed timing. Principal component analysis (PCA) identified multi-dimensional meal timing patterns. Fat mass index (FMI) was estimated using dual energy X-ray absorptiometry. Quantile regression assessed if there were associations between meal timing traits and FMI across the entire FMI frequency distribution. ResultsThe typical first and last eating occasions were 8:00am (40 minutes after waking) and 8:00pm (2.7 hours before sleep), respectively, thus the eating period typically lasted 11.5 hours per day. The typical eating period midpoint was 2:15pm, and the timing when 50% of energy intake was consumed typically occurred at 3:15pm. PCA revealed three meal timing patterns: 1) "Delayed Start, Condensed Eating Period" (43% of variance; shorter eating period and delayed timing of first eating); 2) "Late, Sleep Proximal Eating" (30% of variance; later timing of last eating and extended eating period), and 3) "Later Energy Intake" (10% of variance; delayed energy intake midpoint). Higher scores for the "Delayed Start, Condensed Eating Period" pattern associated with higher body mass index and FMI at the upper tails of their distributions. ConclusionsDistinct multidimensional meal timing patterns emerged in early adolescence, with the delayed start, condensed eating period pattern potentially associated with higher adiposity. Clinical Trials Registry Site and NumberN/A

Flavor-nutrient learning (FNL) refers to learning associations between a foods flavor and the rewarding appetition signals that arise from post-oral nutrient sensing during or after a meal. In rodent models FNL reliably produces strong flavor preferences and increased intake of nutrient-paired flavors, implicating FNL as a presumptive obesogenic influence in the modern environment. However, evidence that FNL plays a causal role in diet-induced obesity is ambiguous. We have previously shown that degree of weight gain on a high-fat/sugar diet is associated with stronger FNL responses, but direction of causation was unclear. This paper reports three experiments investigating whether individual differences in FNL conditionability are linked to obesity proneness prior to obesity onset. Two experiments comparing selectively-bred obesity-prone vs resistant strains found no strain differences in FNL. A third study in lean, outbred rats evaluated whether baseline individual differences in FNL prospectively predict weight gain on a cafeteria diet. Unexpectedly, rats who showed the strongest learned increase in intake of a nutrient-paired flavor subsequently gained the least weight when switched to cafeteria diet, suggesting FNL protects against weight gain. In fact, individual differences in FNL explained a portion of variance in cafeteria weight gain over and above measured kcal intake, implying a function for FNL in adaptively modulating metabolic responses to energy intake. Collectively, several studies have now shown individual differences in obesity proneness to be either positively correlated, uncorrelated, or negatively correlated with FNL, calling for a more nuanced view of how appetition influences intake and energy balance.

Background: Repeated metabolic-bariatric surgery (MBS, r-BS) represents 10-25% of all MBS procedures and is commonly performed for recurrent weight gain after initial weight loss. How weight loss followed by regain reshapes adipose tissue biology remains unclear. We hypothesized that women undergoing r-BS exhibit a distinct adipose tissue signature compared with those undergoing primary bariatric surgery (p-BS). Methods: We analyzed subcutaneous and visceral adipose tissues (SAT, VAT, respectively) from women undergoing either p-BS, or r-BS with documented >15% weight loss after prior MBS. Tissues were assessed histologically, molecularly, and functionally (activation of human microglia cells (HMC3) by SAT secretome). Results: Consistent with other cohorts, women undergoing r-BS (n=21) trended to be older (47.2 vs. 40.5 y, p=0.06) than those undergoing p-BS (n=35), with a lower BMI (42.3 vs. 45.6 kg/m2, respectively, p=0.103), and a trend for improved cardiometabolic risk parameters such as fasting insulin, CRP and HDL-c. Adipose tissue histological features (adipocyte size, fibrosis, macrophage and crown-like structure abundance) were similar, while adipose mast cells were slightly (though insignificantly) more prevalent in r-BS. A single-nucleus RNA-seq-based deconvolution algorithm applied to bulk RNA-seq confirmed the absence of a major shift in adipose tissue cell-type composition. Yet, it uncovered a unique SAT transcriptome, with activation of inflammatory pathways in r-BS. Consistently, SAT explants from r-BS secreted higher protein concentrations of NFkB-regulated cytokines IL6 and IL8. Biological impact of the more inflammatory secretome was demonstrated by its increased ability to activate human microglia cells. Conclusions: Prior BS with significant weight loss-regain in women is associated with an inflammatory SAT transcriptome and secretome, possibly reflecting altered adipose-brain endocrine communication.

Background Diverse epigenetic clocks are known to capture health risks associated with increased adiposity, but their estimates have never been combined to represent a holistic estimate of biological age acceleration (BAA). There is also a gap in research using epigenetic clocks to study adiposity in lower-middle income Asian countries. Methods and Findings Data from 1,745 participants (21.7{+/-}0.3 years old, 45% female) of the Cebu (Philippines) Longitudinal Health and Nutrition Survey were analyzed. BAA was calculated using PCHorvath 2, PCHannum, PCPhenoAge, PCGrimAge, PCDNAmTL, and DunedinPACE. After ascertaining suitability for factor analysis (Kaiser-Meyer-Olkin 0.81), factor analysis was used to create PCFactorAge. Analogously, FactorAge was created using Horvath, Hannum, PhenoAge, GrimAge, DNAmTL, and DunedinPACE. BMI, waist circumference (WC), and waist-to-height ratio (WHtR) were used to represent adiposity. Linear regression was used to test the association of each adiposity measure with each BAA measure. BMI, WC, and WHtR were positively associated with both BAA combinations: 5 kg/m2 higher BMI corresponded to 0.097 (p=0.015) standard deviation (SD) increase in FactorAge and 0.099 (p=0.004) SD increase in PCFactorAge; 10 cm increase in WC--with 0.091 (p=0.005) SD increase in FactorAge and 0.094 (p<0.001) SD increase in PCFactorAge; 0.1 increase in WHtR--with 0.164 (p=0.001) SD increase in FactorAge and 0.163 (p<0.001) SD increase in PCFactorAge. Additionally, WHtR was associated with meaningful increases in PhenoAge, PCPhenoAge, PCHorvath 2, PCHannum, PCGrimAge, and DunedinPACE. WC was positively associated with PCHorvath 2, PCHannum, PCPhenoAge, and DunedinPACE. BMI was positively associated with PCHannum, PCPhenoAge, and DunedinPACE. Conclusions Our study presents a novel approach to creating a BAA estimate using multiple epigenetic clocks and shows that adiposity measures predict this factor in a young Filipino cohort.

Importance: Glucagon like peptide 1 receptor agonists (GLP 1 RAs) and dual glucose dependent insulinotropic polypeptide/glucagon like peptide 1 receptor agonists have demonstrated what may be considered transformative efficacy in recent randomized clinical trials for the treatment of obesity, yielding substantial weight loss in a majority of participants. However, the extent to which these trial results translate into routine clinical practice particularly within the rapidly expanding direct to consumer (DTC) telehealth sector serving self pay populations remains insufficiently characterized. As access to and affordability of these therapies broaden beyond traditional insurance based care models, evaluating real world effectiveness, safety, and patient engagement among individuals shouldering the full financial cost of treatment is essential for informing future models of obesity care delivery. Objective:To assess long term medication specific weight loss outcomes, including gender specific responses and discrepancies, and explore usage trends in a real world, self pay telehealth cohort receiving GLP 1 RA therapy, using an Observational study design (Retrospective data analysis). Setting and Participants:Retrospective data of patients enrolled in electronic health records (EHR) from Carevalidate, a national US telehealth platform provider for Online TeleHealth companies. The data collected ranged for a total of 703 days from January 12, 2024, to December 15, 2025. The analysis included 572 adults with overweight or obesity diagnosis who initiated treatment with semaglutide or tirzepatide and completed a minimum of 9 months of active follow up. Patients with insufficient follow up or those utilizing insurance coverage were excluded to isolate the self pay phenotype. Exposures: Prescription of semaglutide or tirzepatide (injectable or oral formulations) via synchronous or asynchronous telehealth consultations, titrated according to standard clinical protocols adapted for patient tolerance and financial sustainability. Main Outcomes and Measures: The primary outcome was percentage total body weight loss (%TBWL) from baseline to the last recorded encounter. Secondary outcomes included categorical responder rates (5%, 10%, 15%, >20% weight loss), weight loss velocity analysis, and telehealth utilization metrics (frequency of encounters and visit intervals) including gender differences in approaching the telehealth program. Results: The final analytical cohort included 572 patients (79.2% female; 20.8% male). Overall, 95.8% (548/572) achieved weight loss, while 3.7% experienced weight gain. At 12 months, the mean %TBWL was 13.8% for the semaglutide cohort (n=450) and 12.5% for the tirzepatide cohort (n=122), with no statistically significant difference between the two medications (P >.05), contrary to standard clinical trial data suggesting tirzepatide superiority. A significant gender difference was observed: females were significantly more in number comprising 80% of the cohort and were likely to be "major responders" (>20% weight loss) compared to males (29.8% vs 5.9%; P <.001). Conversely, males demonstrated significantly higher utilisation rates, attending more frequent encounters (mean 13.5 vs 12.7; P =.028) with shorter intervals between visits (35.6 vs 44.1 days; P =.009) compared to females. Weight loss velocity for both medications peaked during months 1 to 3 (~1.07 lbs/week) and declined substantially by months 12 to 15, indicating a plateau effect independent of the specific agent used. Conclusions and Relevance: Telehealth-managed GLP 1 treatment in a self pay population demonstrates high efficacy comparable to clinical trials for semaglutide. However, tirzepatide outcomes fell short of trial benchmarks, likely due to economic barriers preventing optimal dose titration and lower sample size. The study identifies a discrepancy where females approach the telehealth based self pay system more but males engage more frequently with the digital platform which could be due to inferior physiological outcomes ( less weight loss and more non responders) compared to females.This suggests that while telehealth is a viable model for long term obesity care, the "one size fits all" approach may be insufficient for under responders, who may require distinct titration strategies or tailored behavioral interventions to overcome baseline genetic and biological resistance.

BackgroundObesity is a chronic multifactorial disease characterized by substantial interindividual variability in weight loss after lifestyle intervention and bariatric surgery. Thyroid hormones play a key role in energy homeostasis, but their influence on postoperative weight outcomes remains insufficiently studied. ObjectiveTo evaluate the association between preoperative thyroid status and changes in body mass index (BMI) after lifestyle intervention and bariatric surgery over a five-year follow-up. MethodsWe conducted a retrospective cohort study including adults with class II or III obesity enrolled in the Obesite Severe et Epigenetique (OBESEPI) study. All participants underwent preoperative lifestyle intervention followed by bariatric surgery. Thyroid status was classified as euthyroid or hypothyroid based on clinical and biochemical criteria. BMI was assessed at baseline and at nine postoperative time points over five years. ResultsAmong 435 included patients, 71 (16.8%) had hypothyroidism. Baseline BMI was similar between groups, whereas diabetes was more frequent in hypothyroid patients (52.1% vs 37.7%; p = 0.022). Hypothyroid patients had significantly higher BMI at 6-24 months after surgery, but differences were no longer significant beyond three years. BMI trajectories and magnitude of weight regain were comparable between groups. Higher preoperative TSH levels were independently associated with BMI regain (OR 1.32, 95% CI 1.00-1.72; p = 0.047). Higher baseline BMI, younger age, and female sex were also associated with greater BMI regain. ConclusionsHypothyroidism was associated with lower early postoperative weight loss but did not influence long-term BMI trajectories. Higher preoperative TSH levels were independently associated with BMI regain. KEYPOINTSO_LIPreoperative hypothyroidism is associated with reduced early weight loss during the first two years after bariatric surgery. C_LIO_LILong-term BMI trajectories and weight regain patterns are similar between hypothyroid and euthyroid patients beyond three years of follow-up. C_LIO_LIHigher preoperative TSH levels independently predict BMI regain. C_LIO_LIBaseline BMI, younger age, and female sex remain key determinants of the magnitude of BMI regain after bariatric surgery. C_LI

BackgroundObesity arises from a complex interplay of genetic and environmental factors, with alterations of transcriptional networks that integrate metabolic, immune, and regulatory pathways. Conventional measures such as body mass index (BMI) quantify body size but fail to capture the molecular heterogeneity underlying divergent metabolic outcomes. We therefore sought to construct a gene expression-based transcriptomic representation of obesity, using BMI as a practical training anchor, and to use this framework to delineate transcriptional programs associated with metabolically healthy and pathogenic obesity, with subsequent projection to mouse transcriptomic data for cross-species validation. MethodsTranscriptome data of human visceral adipose tissue (N= 1,298) were used to derive the transcriptomic BMI model, and genes contributing to the model were functionally annotated by gene set enrichment analysis. The human-trained model was subsequently applied to mouse selection lines (N = 18) with divergent obesity phenotypes. In the human cohort, post hoc stratification into metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) groups was performed using a downstream classification framework incorporating observed BMI together with predicted BMI, to assess whether model-derived predicted BMI reflected obesity-related pathophysiologic status. ResultsModel-selected genes were involved in coordinated regulation of lipid metabolism, immune activation, and growth signaling, extending to mitochondrial and translational pathways. Cross-species analyses uncovered conserved metabolic polarization: DU6 mice exhibited lipid-anabolic and inflammatory remodeling, whereas DU6P mice displayed oxidative, mitochondrial, and GH-axis-enriched transcriptional states. In human cohorts, MHO individuals showed upregulation of mitochondrial energetics and protein synthesis, while MUO individuals were characterized by increased autophagy, lipid catabolism, and stress-adaptive signaling on the transcriptional level. Together, these findings define a conserved molecular continuum linking oxidative efficiency to metabolic health and inflammation to metabolic vulnerability. ConclusionsThis integrative transcriptomic framework bridges human and mouse adipose biology to uncover conserved mechanisms underlying obesity phenotypes. By contrasting mitochondrial and translational programs with inflammatory and catabolic pathways, it provides mechanistic insight into metabolic resilience and a foundation for precision approaches to obesity management.

BackgroundObesity disrupts type 2 immune cell populations in white adipose tissue, replacing the homeostatic network of group 2 innate lymphoid cells (ILC2s), eosinophils, T helper 2 (Th2) cells, and alternatively activated macrophages (AAMs) with pro-inflammatory type 1 populations. Whether this remodelling reflects permanent immune impairment or a reversible shift in cellular equilibrium, and to what extent bariatric surgery restores type 2 immunity, remain incompletely understood. MethodsWe performed comprehensive immunophenotyping of visceral white adipose tissue (WAT) and peripheral blood from persons with severe obesity (people with obesity, PWO) scheduled for or having undergone bariatric surgery (sleeve gastrectomy, gastric bypass), combined with lean controls. Using flow cytometry, quantitative PCR, and in vitro polarization assays, we assessed immune cell frequencies, transcription factor expression, cytokine profiles, and functional polarization capacity across lean, pre-operative, and post-operative states. ResultsObesity was associated with decreased eosinophil and CD8+ T cells frequencies in WAT, accompanied by an increase in CD4+ frequency and a shift from Th2 toward Th1 predominance, as well as elevated PD-1 expression on T cell subsets. Bariatric surgery partially normalised peripheral immune cell composition, reducing CD8+ T cell frequencies while increasing CD4+ T cells. Macrophage polarization capacity, dampened in pre-operative PWO, recovered after surgery. Conversely, Th2 polarization capacity and IL-13 production were reduced in post-operative T cells despite preserved function pre-operatively, indicating divergent trajectories of innate and adaptive immune reconstitution. ConclusionType 2 immune cells retain functional plasticity in human obesity despite reduced frequency. Bariatric surgery differentially reconstitutes immune function, restoring macrophage plasticity while paradoxically reducing Th2 polarization capacity, arguing against uniform immune normalisation after weight loss. FundingGerman Federal Ministry of Research, Technology and Space (BMFTR, FKZ 01KI2109), Interdisciplinary Center for Clinical Research (IZKF, Faculty of Medicine, Friedrich-Alexander Universitat (FAU) Erlangen-Nurnberg).

BackgroundPsychiatric conditions, eating disorders (EDs), and exposure to violence are highly prevalent in patients with severe obesity. However, their association with postoperative weight trajectories following bariatric surgery remains unclear. ObjectiveTo assess the associations between eating disorders, psychiatric conditions, and history of violence with multiple dimensions of weight trajectory after bariatric surgery. MethodsThis retrospective study included 414 patients with severe obesity from the OBESEPI cohort who underwent bariatric surgery at Nancy University Hospital (France). Psychological factors were assessed using a standardized preoperative psychiatric interview. Weight outcomes included preoperative BMI change, maximal BMI loss ({Delta}BMImax), final BMI change (dBMIdf), weight regain (BMIR), and magnitude of weight regain (dBMIR). Multivariable linear and logistic regression models were adjusted for age and sex. ResultsPsychological factors were not associated with baseline BMI or preoperative BMI variation. A history of violence was significantly associated with greater maximal BMI loss ({beta} = 1.99, 95% CI [0.73-3.26]; p = 0.002) and greater final BMI reduction ({beta} = 1.81, 95% CI [0.47- 3.14]; p = 0.009). Eating disorders and psychiatric conditions were not associated with weight loss outcomes. No association was observed between overall exposure to violence and weight regain. However, subtype analyses showed that physical violence was associated with a higher risk of weight regain, whereas psychological violence was associated with a lower risk. No significant associations were found for the magnitude of weight regain. ConclusionsEating disorders and psychiatric conditions were not associated with postoperative weight outcomes in this cohort. In contrast, exposure to violence--particularly when differentiated by subtype--was associated with distinct patterns of weight loss and regain. These findings highlight the relevance of trauma-informed assessment in bariatric care and support a more individualized approach to obesity management.

Objective Fatty Acid esters of Hydroxy-Fatty Acids (FAHFAs) are anti-diabetic and anti-inflammatory lipokines produced mainly by adipose tissue (AT). As exercise training enhances FAHFA levels, we investigated the impact of acute exercise (AE) and exercise-mimicking conditions on circulating and adipocyte FAHFA levels. Methods Clinical trial (NCT05572905) in 60 women, grouped by BMI (lean vs. obese) and age (young vs. older), was combined with in vitro experiments on human adipocytes. Following baseline characterization (body composition, VO2max, insulin sensitivity, AT/plasma FAHFAs), women underwent a cross-over AE and control interventions with repeated blood sampling for FAHFA analysis. Results In AT, lean and older women exhibited higher FAHFA levels than obese and young women, respectively; older women also showed a shift toward higher levels of 13/12-carbon-branched FAHFAs. Circulating FAHFA levels were similar across all groups and were not positively associated with insulin sensitivity, VO2max or FAHFA levels in AT. Although AE increased circulating free fatty acids (FFA), plasma FAHFAs dropped in response to both AE and control interventions. In adipocytes, FAHFAs were unaffected by glucocorticoids but increased in response to lipolysis together with gene expression related to FFA oxidation (FAO). Nevertheless, blocking mitochondrial FAO partially mimicked the lipolytic effect, while peroxisomal inhibition synergistically boosted FAHFA lipolysis-driven production despite having no effect alone. Conclusions While adiposity and aging modulate FAHFA levels in AT, circulating levels remain stable and unaffected by AE, challenging subcutaneous AT as their primary systemic source. In vitro, FAHFA synthesis is driven by high FFA availability but limited by competing peroxisomal FAO.

Background: C-terminal binding protein 2 (CtBP2) has been implicated in metabolic regulation, but its association with specific measures of adiposity and lipid profiles in humans remains unclear. This study examined the relationship between circulating CtBP2 levels and key components of metabolic syndrome, focusing on body fat distribution and lipid markers. Methods: Data from 508 participants (259 men, 249 women) from a publicly available dataset were analyzed. Serum CtBP2 concentrations were measured using ELISA. Associations with obesity markers (BMI, waist circumference, waist-to-hip ratio) and lipid profiles (triglycerides, HDL cholesterol) were assessed using Spearman correlation and linear regression, adjusting for age and sex. Results: CtBP2 levels showed weak but statistically significant positive correlations with all measures of adiposity, with the strongest association observed for waist circumference ({rho} = 0.150, p < 0.001), followed by BMI ({rho} = 0.120, p = 0.007) and waist-to-hip ratio ({rho} = 0.098, p = 0.027). No significant correlations were found with triglycerides or HDL cholesterol. In the regression model predicting BMI, age, and sex were significant predictors, while CtBP2 demonstrated a trend toward association ({beta} = 0.080, p = 0.052). Conclusion: Circulating CtBP2 appears to be modestly associated with measures of adiposity, particularly abdominal fat, but not with lipid abnormalities. These findings suggest a potential role for CtBP2 in obesity-related metabolic dysregulation and underscore the need for further mechanistic studies to clarify its clinical relevance.

IntroductionEating behaviors are consistently associated with weight-related traits, yet the biological factors contributing to individual differences in these behaviors remain poorly characterized. Plasma proteomics offers an opportunity to investigate the biological processes underlying eating behaviors. MethodsParticipants were 730 young adult twins from the FinnTwin12 cohort. Eating behaviors were measured through self-report questionnaires, including the Three-Factor Eating Questionnaire-R18 and four additional items on eating styles. Associations between plasma proteins and eating behaviors were examined using generalized estimating equation models adjusted for age and sex, with additional analyses adjusting for body mass index (BMI). Within-pair analyses were conducted in both monozygotic (MZ) and dizygotic twin pairs to assess whether associations were influenced by genetic or environmental factors. ResultsWe identified 51 significant protein-eating behavior associations involving 35 unique proteins (FDR <0.05). We observed 19 associations for the item "overeating when feeling down" and 12 for the TFEQ factor of emotional eating. The identified proteins were predominantly enriched in immune system pathways, including the complement cascade and adaptive immune signaling. After further adjustment for BMI, 12 associations persisted, most of which were associated with eating-style items, suggesting that BMI had a substantial influence on protein-eating behavior associations. Within-pair analyses of MZ pairs indicated that several associations persist after accounting for genetic effects. ConclusionOur study identifies plasma proteins associated with eating behaviors, largely involving immune-related pathways. While some associations attenuated in twin analyses, several persisted, suggesting environmental influences. These results highlight potential biomarker candidates and indicate that modifiable environmental factors may contribute to the proteomic profiles associated with eating behaviors, with possible implications for weight-related traits.

Background Cardiometabolic-based chronic disease (CMBCD) at an individual level results from complex interactions among a multi-tiered network of sociodemographic, behavioral, and metabolic factors. Though a consensus set of risk factors drives CMBCD, population context influences risk factor effects and interactions. To better understand this phenomenon, we investigated the multi-tiered networking of cardiometabolic variables across diverse populations using a comparative modelling approach. Methods and Findings Utilizing nationally representative cross-sectional data from 48 countries participating in the World Health Organization "STEPwise approach to noncommunicable disease risk factor surveillance" survey, we learned country-specific Bayesian networks including sociodemographic, behavioral, and cardiometabolic variables (adiposity, diabetes, hypertension, hyperlipidemia, and cardiovascular disease). By computing the structural Hamming distance between pairs of networks, we compared differences in network structures across regions and country income levels. We then used the learned networks to assess individual risk factor influences and interactions on cardiometabolic outcomes. Country-specific Bayesian networks varied in terms of the risk factors directly and indirectly associated with the cardiometabolic outcomes. Network structures differed significantly across regions (p = 0.023) but not across income levels (p = 0.91). These results were robust to an alternative learning algorithm, network comparison metric, and data imputation approach. Older age (60+ vs. 30-44 years old) was associated with a greater increase in probability of obesity in Europe and Central Asia (+80%) compared to other regions. Higher education was associated with increased probability of obesity (+53%), diabetes (+18%), and hypertension (+2%) in South Asia but decreased probability of obesity (-10%), diabetes (-32%), hypertension (-16%), and hyperlipidemia (-25%) in Middle East and North Africa. The interaction between age and sex in predicting obesity was significant in the highest proportion of countries in Europe and Central Asia compared to other regions. While this dataset provided standardized data across multiple countries to define cardiometabolic risk factors and drivers, there was limited data on certain health outcomes and uneven availability of data across regions. Conclusions These results revealed specific regional patterns of multi-tiered cardiometabolic risk structures, emphasizing the need for regionally tailored public health strategies rather than applying generalized consensus evidence-based models. Future research should explore the structural drivers of regional differences in inter-relationships of cardiometabolic risk factors, drivers, and disease.

BackgroundPredictors of arterial health impairment from childhood to adolescence remain largely unknown. We investigated associations of childhood cardiometabolic risk factors with several measures of arterial health in adolescence. MethodsAltogether, 222 children were examined at age 7-9 years and eight years later at age 15-17 years. Body fat percentage (BF%), glucose, insulin, lipids, blood pressure (BP), and inflammation biomarkers were measured and homeostatic model assessment for insulin resistance (HOMA-IR), a metabolic syndrome score (MetSscore), and an inflammation score were calculated at baseline. Pulse wave velocity (PWV) and cardio-ankle vascular index (CAVI) were assessed using impedance cardiography and carotid intima-media thickness (cIMT), carotid distensibility (cDIST), Youngs elastic modulus (YEM), and stiffness index (SI) using ultrasonography. Associations of childhood cardiometabolic risk factors with measures of arterial health were analyzed using linear regression models adjusted for childhood age and sex. ResultsBF% was positively associated with PWV (standardized regression coefficient {beta}=0.207, p=0.008), CAVI ({beta}=0.171, p=0.031), cIMT ({beta}=0.146, p=0.034), and YEM ({beta}=0.164, p=0.016). HOMA-IR was positively associated with PWV ({beta}=0.242, p=0.001) and CAVI ({beta}=0.216, p=0.004) and inversely with cDIST ({beta}=-0.162, p=0.015). MetSscore was positively associated with PWV ({beta}=0.266, p<0.001), CAVI ({beta}=0.219, p=0.004), and YEM ({beta}=0.141, p=0.032) and inversely with cDIST ({beta}=-0.140, p=0.035). SBP was positively associated with PWV ({beta}=0.257, p<0.001) and YEM ({beta}=0.156, p=0.018) and inversely with cDIST ({beta}=0.169, p=0.012). ConclusionIncreased adiposity, insulin resistance, elevated SBP, and cardiometabolic risk factor clustering in childhood association of arterial stiffness and reduced arterial distensibility in adolescence, emphasizing prevention of cardiovascular diseases since childhood.

Background and aims: Direct evidence to connect early life metabolism with cardiometabolic diseases in old age is limited due to the rarity of multi-decadal biochemical follow-up studies. To gain deeper insight into metabolic ageing, we conducted a longitudinal study that integrates serial data on clinical biomarkers, metabolomics and clinical events across the human life course. Methods: Children born in 1962-1992 were included from four European cohorts. Time-series of clinical biomarkers and metabolomics data were available for 8,653 participants (ages 0-49 years, 142 molecular and four physiological variables). Comparable data for 13,795 UK Biobank participants at two visits (ages 40-79 years) were linked with retrospective and prospective records of diabetes and cardiovascular disease. Lifetime metabolic trajectories were reconstructed by unsupervised machine learning and local polynomial regression. Results: A stable stratification in metabolic health emerged in children between ages 3 and 12 years and persisted to old age. We summarized this population pattern by assigning each participant into one of seven metabolic subgroups with characteristic biomarker trajectories. Two subgroups (MetDys TG+ and MetDys TG-) featured increased waist-height ratio from childhood, persistently higher C-reactive protein throughout life and rapidly increasing fasting insulin between 30 and 49 years of age. Both subgroups exhibited high risk for diabetes (HR > 13) and ischemic heart disease (HR > 2.5) when compared against the lowest risk subgroup (High HDL ApoB-). Conclusions: This life-course analysis shows that metabolic dysfunction associated with excess weight gain begins in early childhood and is associated with cardiometabolic morbidity in later life.

Background Early onset obesity in children, almost always accompanied by significant health complications, may be driven by rare genetic variants that influence appetite, metabolism, and nutrient absorption. Traditional treatment approaches are usually insufficient for those with monogenic obesity of this type. Glucagon-like peptide-1 (GLP-1) receptor agonists, such as semaglutide, and related drugs such as melanocortin 4 receptor agonists, have emerged as promising first-line treatments for severe obesity. There is no established protocol or pathway in England for identifying children with monogenic obesity who could benefit from these and similar treatments Methods We undertook early economic modelling to examine the cost-effectiveness, from a health service perspective, of implementing a new pharmacotherapeutic care pathway for the identification and treatment of monogenic obesity in children. We modelled a hypothetical population of children with hyperphagia and body mass index (BMI) three standard deviations above mean values for age and sex. We evaluated the clinical decision to initiate the pathway using a decision tree model with patient quality-adjusted life years (QALYs) and NHS healthcare costs 12 months from an initial clinic visit as outcomes, and calculated incremental cost effectiveness ratios and a cost-effectiveness acceptability curve. Results Both costs and QALYs were higher under further investigation (GBP3,247 and 0.47 QALYs) compared to no further investigation (GBP1,589 and 0.24 QALYs). The incremental cost-effectiveness ratio in the base case was GBP7,133 per QALY. Further examination of these children was therefore likely to be cost effective in this model. Conclusion A decision-tree model suggested that further investigation of severely obese children potentially eligible for treatment with semaglutide is likely to be cost-effective for the NHS. However, this result is associated with uncertainty arising from a lack of evidence for many key model parameters.

Objectives To estimate population-level eligibility for glucagon-like peptide-1 receptor agonist (GLP-1RA) medications among adults in Australia, according to Therapeutic Goods Administration (TGA) approved indications for chronic weight management and secondary prevention of cardiovascular disease. Design Cross-sectional analysis of data from the Australian Bureau of Statistics 2022 National Health Survey. Setting, Participants Non-pregnant adults [&ge;] aged 18 years who are usual residents of Australia and living in a private dwelling. Main outcome measures Total number of adults who are eligible for GLP-1RA medications according to TGA approved indications for chronic weight management and secondary prevention of cardiovascular disease, across subgroups defined by body mass index, weight-related comorbidities, and/or socio-demographic factors. Results In total, 39.7% (95% CI 38.4 - 41.0%) of adults in Australia are eligible for GLP-1RA use for chronic weight management, accounting for 7.8 million (95% CI, 7.6 - 8.1 million) individuals. Among those eligible under this indication, 2.9 million (95% CI 2.7 - 3.1 million) adults had no weight-related comorbidities, 3.3 million (95% CI 3.1 - 3.4 million) adults had at least 1 weight-related comorbidity, and 1.7 million (95% CI 1.6 - 1.8 million) adults had at least 2 weight-related comorbidities. The proportion of adults eligible under this indication varied across clinical and sociodemographic factors. Among those eligible under the chronic weight management indication, up to 338.9 thousand (95% CI 271.3 - 406.5 thousand) adults also meet the indication for secondary prevention of cardiovascular disease. Conclusions More than one third of Australian adults are eligible to access GLP-1RAs for chronic weight management, with 3.7-4.3% of adults also qualifying according to the indication for established cardiovascular disease. This study provides a valuable reference to allow policy makers to understand the number of adults in Australia that may benefit from access to GLP-1RA medications under a range of coverage scenarios.