International Journal of Obesity

Background: Ethnic 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. Methods: This cohort sampled 10,350 White and South Asian children born in Leicestershire, 1985-1997. We included 5,571 participants with [≥]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. Results: We 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], [≥]4 vs 0-3 hours/week) and adolescent onset overweight (0.75 [0.59-0.94]). Conclusion: BMI 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

Background and AimSocioeconomically disadvantaged people are more likely to have high body mass index (BMI). However whether socioeconomic position moderates genetic susceptibility to high BMI, and whether this effect differs by sex, remains unclear. We aimed to investigate whether educational attainment (EA) moderates the association between genetic liability for high BMI and BMI trajectories across adulthood in females and males. MethodsWe analyzed data from 69,314 participants in the Trondelag Health Study (HUNT), a population-based cohort with genotyping and repeated BMI measures. A polygenic index for BMI (BMI PGI) was calculated, and participants were categorized by EA level. Using linear mixed-effects models stratified by sex, we tested the interaction between BMI PGI, EA, and age on BMI trajectories. ResultsThe relationship between BMI PGI and BMI was non-linear, showing a steeper slope in the upper deciles, and was modified by sex (p<0.001). Sex-stratified analysis showed that EA moderated the effect of BMI PGI on BMI in females (p=0.003) but not in males (p=0.089). Among highly educated females, the BMI difference between the top and bottom BMI PGI deciles was-0.99 kg/m{superscript 2} [95%CI: -1.67 to -0.30] smaller than among those with low education. In males, the corresponding difference was -0.16 kg/m{superscript 2} [-0.71 to 0.39]. Genetic influences on BMI trajectories showed consistent age-dependent patterns across all educational groups, though trajectories differed by sex. Females experienced a steady increase in BMI until age 60, after which it declined. Males had an early rapid increase, then stabilization, followed by a slight late-life decline. ConclusionHigher EA consistently moderates the effect of genetic liability for high BMI in females throughout adulthood, but this protective effect is absent in males. This sex difference suggests that gender-related socioeconomic factors may modulate the expression of BMI-related genetic variants, warranting further investigation into the underlying mechanisms.

IntroductionMechanistic research has shown that prior obesity induces durable transcriptomic and epigenetic reprogramming in adipose tissue that persists after weight loss and predisposes individuals to weight regain. This phenomenon, termed obesogenic memory (OM), is currently conceptualized primarily as a molecular process. We propose extending OM beyond adipose tissue biology to include interacting biological and sociocultural processes through which past exposures shape present physiological regulation and health-related behavior. MethodsIn-depth qualitative interviews were conducted with individuals living with obesity (n=31) and with healthcare professionals (n=18). The data were analyzed abductively to examine participants lived experiences of obesogenesis. ResultsWe developed a three-phase model of OM comprising memorizing, remembering, and rescribing. The memorizing phase describes the initial acquisition and encoding of biological and sociocultural obesogenic influences. The remembering phase captures the persistence of these influences, contributing to long-term obesity maintenance. The rescribing phase refers to processes through which obesogenic influences may be attenuated or reversed, creating conditions for sustainable health behavior change. ConclusionExtending OM to include sociocultural dimensions provides a more comprehensive understanding of obesity persistence. This integrative framework identifies multilevel targets for obesity prevention and treatment that acknowledge past exposures while supporting resilience and long-term weight management.

The prevalence of obesity is rising worldwide in young people and is associated with poor long-term health outcomes. To counter obesity, weight loss strategies especially involve changes in feeding behaviors and food choice. However, the high level of relapse to unhealthy dietary habits represents an important challenge, suggesting long-term alterations of decision-making and food-seeking processes. Previous studies showed that adolescence is critical for the development of decision-making functions. Thus, it is essential to understand the precise impact of the exposure to obesogenic diets during this life stage on the different processes underlying flexible control of food-seeking actions. To address this, we gave mice access to high-fat diets (HFDs) with different fat contents during adolescence and investigated the long-lasting impact on action control at adulthood after a switch to a healthy diet. We uncovered important sex differences. In both males and females, exposure to HFD with very high-fat content (60%) promote inflexible habitual behavior, which is less flexible to adapt to changes in outcome value or action-outcome relationships. In contrast, exposure to HFD with lower fat content (45%) impaired action control based on the updating of outcome value in males only, while impairing action control based on the updating of action-outcome relationships in females only. These findings highlight how the consumption of obesogenic diets during adolescence has long-lasting, diet- and sex-dependent effects on decision-making processes, promoting habitual responses to food. These changes may support long-term vulnerability for mental and physiological health conditions.

Background: The 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. Objective: We 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. Methods: We 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. Results: The 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. Conclusions: Distinct multidimensional meal timing patterns emerged in early adolescence, with the delayed start, condensed eating period pattern potentially associated with higher adiposity.

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 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.

BackgroundEvidence on how leisure-time physical activity (LTPA) improves lifetime body mass index (BMI) remains fragmented and prone to confounding. MethodsWe pooled 14,993 adults (30-90 y; 52.7% women; cohorts: REGICOR-ACRISC, ILERVAS, ARTPER) with baseline estimated LTPA (moderate-to-vigorous LTPA [MVLTPA] in REGICOR-ACRISC), genotype, and repeated BMI values from electronic health records (1990-2024, 36,157 measures). LTPA was categorized into cohort-specific quartiles; MVLTPA in 0, <100, <200, and [&ge;]200 METs-min/day. In one-sample Mendelian randomization analyses, we categorized participants in quartiles of a cardiorespiratory fitness polygenic risk score derived from a large GWAS in UK Biobank. Group-dependent BMI trajectories were modeled using spline mixed-effects models. Obesity onset (first BMI [&ge;]30 kg/m2) was analyzed with IPW-weighted Kaplan-Meier curves and Cox models. ResultsHigher LTPA was associated with slower BMI increases in ages 30-60 (Q1: +0.120 vs Q4: +0.075 kg/m2{middle dot}year), slower declines in ages 70-90 (Q1: -0.143 vs Q4: -0.123 kg/m2{middle dot}year), and lower obesity risk (Q4 vs Q1: HR 0.83, 95% CI 0.72-0.96). Similar trends were observed for MVLTPA. Higher genetically determined cardiorespiratory fitness showed parallel gradients (ages 30-60, Q1: +0.109 vs Q4: +0.101 kg/m2{middle dot}year; ages 70-90, Q1: -0.130 vs Q4: -0.102 kg/m2{middle dot}year) and lower obesity risk (Q4 vs Q1: HR 0.66, 0.56-0.78). Associations were present for women and men separately, but were stronger in men. ConclusionsHigher LTPA and MVLTPA were associated with more favorable lifelong BMI trajectories, delayed obesity risk, and convergent support from Mendelian randomization analyses, supporting a causal protective role of physical activity (in both sexes but stronger in men).

BackgroundPrevious studies have presented conflicting findings regarding the potential causal relationships between leisure-time physical activity (LTPA) and body mass index (BMI). Here, we use individual-level data and apply a triangulation framework that incorporates three complementary methods to investigate the bidirectional causal associations between LTPA and BMI. MethodsWe used data from a longitudinal Finnish twin cohort with four measurement points spanning 36 years. The data included 22,696 twin individuals aged 18-50 years at baseline (52.4% women); 8,527 had genetic data available. We applied three analytical approaches suggested to strengthen causal inference in observational studies: Random intercept cross-lagged path model (RI-CLPM) for longitudinal data, one-sample Mendelian Randomization (MR) and Direction of Causation (DoC and MR-DoC) twin models for cross-sectional data at each measurement point. ResultsAll three approaches provided evidence for a causal effect of higher BMI on lower LTPA, particularly at the later follow-up stages. Only twin models suggested a negative causal effect of LTPA on BMI. Men and women showed mainly similar effects. ConclusionsEvidence triangulation across the three methodologies provided support for a causal effect of higher BMI on lower LTPA, whereas the evidence for a reverse effect was less convincing. Our results indicate that the role of high BMI in limiting LTPA becomes more important with advancing age, while also highlighting the importance of accounting for timing when studying the causal effects of LTPA on BMI and vice versa.

Introduction: Eating 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. Methods: Participants 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. Results: We 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. Conclusion: Our 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.

BackgroundVisceral adiposity is widely regarded as the pathogenic component of central obesity in cardiometabolic disease. However, emerging evidence suggests that abdominal subcutaneous adiposity may also confer metabolic risk in South Asian populations, although data in young, lean individuals are scarce. We investigated associations of MRI-measured abdominal subcutaneous adipose tissue (ASAT) and visceral adipose tissue (VAT) with cardiometabolic risk markers in young rural Indian adults. MethodsWe quantified ASAT and VAT using MRI in 590 participants (310 men) aged 18 years from the Pune Maternal Nutrition Study cohort. Sex-specific multiple regression models were used to examine associations with glucose-insulin indices, blood pressure, lipids, adipokines, and inflammatory markers. ResultsASAT showed broad and consistent associations with adverse cardiometabolic profiles, including higher 120-min glucose, dyslipidaemia, elevated blood pressure, leptin, CRP and leukocyte count, and lower insulin sensitivity and adiponectin, particularly in men; in women, ASAT was associated with most cardiometabolic risk markers except HDL-cholesterol. In contrast, VAT was associated with fewer risk markers and exhibited weaker, sex-specific patterns of association. Across outcomes, associations with ASAT were generally stronger than those observed for VAT. ConclusionsIn young, lean Indians, abdominal subcutaneous adiposity exhibits stronger associations with insulin resistance, dyslipidaemia and inflammation than visceral adiposity, challenging the prevailing VAT-centric paradigm derived largely from Western populations. These findings provide human evidence that the hierarchy of metabolic risk across abdominal fat depots is population-specific. This suggests genetic and early-life risk stratification, and supports early targeted preventive strategies. Research InsightsWhat is currently known about this topic? (max. 3 highlights, each < 100 characters) Indians have higher central obesity-adiposity than Europeans at similar BMI. Western data links VAT with cardiometabolic risk, while ASAT is protective. VAT & ASAT risk patterns vary across native and migrant South Asians. What is the key research question? (formatted as a question, < 100 characters) How do VAT and ASAT associate with cardiometabolic risk in lean rural Indian youth? What is new? (max. 3 highlights, each < 100 characters) ASAT shows stronger links with cardiometabolic risk than VAT in rural Indian youth. ASAT may contribute to high diabetes and CVD risk at low BMI in young Indians. How might this study influence clinical practice? (max. 1 highlight, < 100 characters) Early-life ASAT accumulation may raise later cardiometabolic risk, supporting early prevention strategies.

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.

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.

IP3R-Grp75-VDAC1 protein complex at the mitochondria-ER contact sites (MERCS) is involved in response to nutrients and control of glucose and energy metabolism, however, early alterations of the complex and MERCS in response to increased fat intake remain inconclusive. We investigated early effects of high-fat diet (HFD) on IP3R-Grp75-VDAC1 protein expression in correlation with ER-mitochondrial interaction in the liver of mice. Five-week-old mice were fed an HFD or a standard diet (SD) for 2 weeks (2W) or 8 weeks (8W). MERCS fractionation by a gradient ultracentrifugation, Western blot, transmission electron microscopy (TEM), Oroboros high-resolution respirometry were used to analyse liver tissues, while real-time PCR was used to profile genes responsive to HFD. No macroscopic morphological or functional alterations were observed in mice at 2W, while, expectedly, at 8W of HFD mice gained weight and glucose intolerance. Total IP3R protein was reduced at both 2W and 8W points by a post-transcriptional mechanism, while in MERCS, IP3R, VDAC1 and Grp75 were reduced at 8W time-point. TEM analysis revealed a significant reduction of mitochondrial coverage by MERCS, mitochondrial fragmentation and shortening of ER-mitochondria distance already at 2W time-point. Mitochondrial function and metabolism were largely spared. Markers of altered protein homeostasis such as Lmp2, Mecl-1 and Lmp7 showed an early upregulation. In conclusion, HFD induces early alterations in liver MERCS that precede gain of weight and glucose intolerance, suggesting their primary role in obesity and metabolic diseases and as potential therapeutic target.

Obesity is a major contributor to cardiometabolic disease, and pharmacological therapies such as semaglutide are increasingly used to induce weight loss. However, the commonly used diet-induced obesity model in C57BL/6J mice is limited by relative resistance to weight gain in females, complicating the study of sex-specific effects. Here, we used leptin-deficient ob/ob mice, which develop severe early-onset obesity in both sexes, to investigate sex-specific responses to semaglutide on skeletal muscle mass, function, and mitochondrial metabolism. The ob/ob mice were treated daily with semaglutide or vehicle for three weeks, followed by assessments of body composition, muscle and organ mass, muscle contractile function, and mitochondrial efficiency. Semaglutide induced comparable reductions in body weight and food intake in both sexes but elicited distinct sex-specific changes in body composition. Male mice exhibited losses in both skeletal muscle and organ mass, whereas female mice preferentially lost fat and organ mass while preserving skeletal muscle. Despite these divergent structural adaptations, muscle force generation remained intact in both sexes. Collectively, these findings reveal pronounced sexual dimorphism in skeletal muscle and metabolic remodeling during pharmacologically induced weight loss, highlighting the importance of considering biological sex when evaluating the metabolic and therapeutic effects of anti-obesity interventions. Article HighlightO_LIC57BL/6J mice are limited by relative resistance to weight gain in females, complicating the study of sex-specific effects. So, we wanted to determine the sex-specific effect of semaglutide on skeletal muscle function, and mitochondrial metabolism in ob/ob mice. C_LIO_LIWe assessed body composition and ex-vivo muscle force following the treatment and found that the female ob/ob mice are protected from semaglutide-induced skeletal muscle mass loss. C_LIO_LIThese findings demonstrate sex-specific effects of semaglutide, highlighting the need to consider biological sex in GLP-1RA-based therapies. C_LI

BackgroundAcute appendicitis (AA) is a common surgical emergency. Observational studies have reported associations between obesity-related anthropometric traits and AA, but these associations may be affected by confounding and reverse causation. We used Mendelian randomization (MR) to investigate the potential causal effects of body mass index (BMI) and waist-to-hip ratio (WHR) on AA risk. Methods and FindingsWe obtained genome-wide association study (GWAS) summary statistics for BMI (ukb-b-19953), WHR (ieu-a-73), and AA (finn-b-K11_APPENDACUT) from the IEU Open GWAS database. We conducted single-variable MR (SVMR) and multivariable MR (MVMR) analyses. The primary estimator was inverse-variance weighted (IVW) MR, complemented by MR-Egger, weighted median, weighted mode, and simple mode methods. Instrument strength was assessed using the variance explained and F-statistics. Sensitivity analyses included Cochrans Q for heterogeneity, MR-Egger intercept and MR-PRESSO global test for horizontal pleiotropy, leave-one-out analysis, and Steiger directionality testing. We mapped instrumental variants to cis-eQTL genes (eQTLGen) and performed GO and KEGG enrichment analyses. In SVMR, genetically predicted BMI (OR 1.145, P = 0.0006) and WHR (OR 1.336, P = 0.0040) were associated with higher AA risk. Instruments were strong (BMI: [Formula]; mean/min F-statistic= 64.15/29.76; WHR: [Formula]; mean/min F-statistic= 48.41/29.75). Sensitivity analyses did not show strong evidence of heterogeneity or directional pleiotropy, and Steiger tests supported the hypothesized direction (exposure -> outcome). In MVMR including both traits, WHR remained associated with AA risk (OR 1.374, P = 0.0110), whereas BMI was not (P = 0.8000). Enrichment analyses suggested WHR-mapped genes were enriched in pathways related to adipocyte differentiation, while BMI-mapped genes were enriched in terms including nuclear envelope and endocytosis-related pathways. ConclusionsThese MR analyses are consistent with a potential causal relationship between obesity-related traits and AA risk, with WHR showing an association independent of BMI in multivariable models. Further work in diverse populations and with additional sensitivity analyses is warranted to assess robustness to pleiotropy and generalizability.

Many Asian American (AA) subgroups experience disproportionate rates of cardiometabolic (CMB) conditions, yet the contextual drivers of these disparities remain unclear. Little is known about the role of Asian residential segregation, often conceptualized as Asian enclaves, with limited prior work largely ignoring region of origin and nativity. Using six years of population-based survey data from New York City (N>6,000 AAs) linked with multiple sources of community data, we examine how residence in ethnicity-specific enclaves relates to CMB risks (obesity, hypertension, and diabetes), whether these associations differ by nativity, and the extent to which neighborhood socioeconomic conditions, the built environment, social cohesion, and institutional support account for observed associations. Our combined concentration-based and spatial clustering analysis identified five East Asian enclaves and six South Asian enclaves, with no geographic overlap between the two. Logistic regression analyses show that residence in an East Asian enclave was associated with lower odds of obesity (OR=0.63), while residence in a South Asian enclave was linked to higher odds of diabetes (OR=1.42) and hypertension (OR=1.46). These associations were present only among foreign-born individuals. After adjusting for neighborhood characteristics, the lower obesity risk in East Asian enclaves persisted, while elevated risks in South Asian enclaves were partly reduced. Both suggest a role for unmeasured enclave factors, including cultural and food environments. Our findings challenge the view that Asian enclaves are monolithically health-promoting and redirects scholarly attention toward disaggregated approaches to investigating AA health disparities.

BackgroundTime-restricted eating (TRE) has gained popularity for weight loss and metabolic health. While some evidence suggests greater benefits when TRE aligns with circadian rhythms--characterized by early daytime eating and avoidance of nighttime intake, often referred to as early TRE (eTRE), other studies report no meaningful differences between eTRE, other TRE approaches with or without exercise, or calorie restriction (CR), and robust comparative evidence remains limited. AimTherefore, the aim of this network meta-analysis (NMA) is to evaluate the physiological effects of eTRE, midday time-restricted eating (mTRE), late time-restricted eating (lTRE), with and without exercise, CR, and control (without prescribed energy or fasting windows) on anthropometric measures and cardiometabolic markers in adults with cardiometabolic risk factors. MethodsA comprehensive literature search was conducted in four major databases (PubMed, Web of Science, Scopus, and Embase) up to April 24, 2025. A Bayesian NMA was performed, using a control group as the reference comparator across interventions. Treatment effects were expressed as mean differences with 95% confidence intervals. The relative ranking of the included arms on the outcomes was assessed using surface under the cumulative ranking curve, values derived from the NMA, where higher values reflect a higher probability of superior effectiveness. Resultsa total of 40 trials comprising 3259 subjects were included in the analysis. There were significant reductions in most anthropometric measures in all intervention groups compared to control group. Whereas eTRE and eTRE + exercise (EX) significantly improved glucoregulatory outcomes compared to control, eTRE + EX showed superior results over other interventions. ConclusionWhile our results did not detect statistically significant differences between TRE patterns and CR, the consistent SUCRA rankings in favor of eTRE (particularly with exercise) suggest that meal timing may play an important role in metabolic regulation.