Long-term management of body weight and physiological mechanisms of weight regain

Abstract

Overweight and obesity are major global health challenges. Despite progress in behavioral interventions, nutrition, physical activity, pharmacotherapy, and bariatric procedures, weight regain after successful weight loss is a major challenge. Understanding the definition and physiological mechanisms of weight regain is crucial for developing effective strategies to tackle weight regain and reduce cardiometabolic disorders. This review summarizes recent advances in weight loss strategies. We also discuss the metrics used to quantify weight regain, emphasizing the need for standardization to facilitate comparison between studies, and examine weight regain predictors, including demographic and clinical characteristics, behavior, anatomic factors, and biomarkers. The potential physiological mechanisms underlying weight regain, focusing on obesity memory, metabolic adaptation, and gut hormone alterations, are further elucidated. Comprehensively understanding weight regain provides a foundation for developing long-term, personalized strategies and integrating emerging technologies such as artificial intelligence into long-term weight management.

Introduction

The prevalence of overweight and obesity worldwide has more than tripled between 1975 and 2022 and is recognized as one of the world’s most serious public health problems (Shen and Hu, 2025; Zhang et al., 2025a, b; https://data.worldobesity.org/publications/?cat=23). Excess adiposity contributes to increased risks of comorbidities, impaired quality of life, and premature mortality (Harborg et al., 2024; Xu et al., 2026). Clinical benefits can be achieved upon achieving 5% weight loss, and these benefits increase progressively with greater and sustained weight loss (Lingvay et al., 2022). Achieving and maintaining >10% weight loss usually provides larger benefits, including prevention, improvement, or even remission of type 2 diabetes, hypertension, dyslipidemia, polycystic ovary syndrome, sleep apnea, and long-term cardiovascular events, as well as mortality reduction (Yu et al., 2016a; Lean et al., 2018, 2019; Syn et al., 2021; Shan et al., 2024).

Despite these benefits, maintaining weight loss remains a substantial clinical challenge. Although lifestyle intervention is the first-line therapy, long-term efficacy is often constrained by physiological adaptations and poor adherence (Knowler et al., 2009; van Baak and Mariman, 2019). Recent pharmacotherapy advances, particular dual glucose-dependent insulinotropic polypeptide (GIP)/glucagon-like peptide-1 (GLP-1) agonists and dual GLP-1 and glucagon receptor agonist, can induce average weight reductions of >10% at 1 year (Perdomo et al., 2023; Ji et al., 2025). Nevertheless, randomized withdrawal studies of these agents have consistently shown significant weight regain upon discontinuation (Rubino et al., 2021; Wilding et al., 2022), and long-term data regarding their safety, efficacy, and clinical outcomes are awaited. Bariatric surgery is the most effective treatment for substantial and sustained weight loss and metabolic health improvement, yet a large proportion of patients still experience partial weight regain over time. These observations highlight the need to understand the determinants of weight regain after weight loss. Moreover, emerging artificial intelligence (AI)-enabled tools now offer opportunities to personalize weight management by predicting treatment response, optimizing intervention intensity and improving long-term adherence (Pan et al., 2023; Wang et al., 2025).

Therefore, this review summarizes evidence on (i) current advances regarding strategies for weight loss across behavioral intervention, nutrition, physical activity, pharmacotherapy, and bariatric procedures, (ii) metrics and definitions of weight regain, (iii) clinical, behavioral, anatomic, and biological predictors, and (iv) potential physiological mechanisms.

Strategies for weight management

Weight management is important to improve metabolic health (Hu et al., 2023a, b; Xu et al., 2025a, b). Current evidence-based weight management strategies can be summarized into five categories: behavioral intervention, nutrition, physical activity, pharmacotherapy, and bariatric procedures (Figure 1). Lifestyle intervention (behavioral intervention, nutrition, and physical activity) is the foundation of weight management, yet weight regain hampers weight loss. Sustained weight management usually requires ongoing support and adjunct pharmacologic or bariatric procedures for many patients.

Figure 1.

Strategies for weight management.

Behavioral intervention

Intensive, multicomponent, behavioral interventions are recommended to consist of at least 16 sessions within an initial 6 months, including components such as weight self-monitoring, diet and physical activity counseling, problem solving, and goal setting (Wadden et al., 2006; American Diabetes Association Professional Practice Committee, 2025). An increasing number of randomized controlled trials with follow-up duration of >5 years have shown that intensive behavioral interventions achieved superior weight loss and cardiometabolic risk reduction compared with usual care (Knowler et al., 2009; Lindström et al., 2013; Lean et al., 2024; Kokkorakis et al., 2025). However, effectiveness depends on frequent contact, which might be difficult to sustain in primary care due to resource constraints.

Emerging digital health solutions, including AI-assisted programs, are now becoming more available to bridge this gap. In a phase 3, noninferiority randomized clinical trial, a fully-automated AI-led diabetes prevention program (DPP) achieved noninferior effects (risk difference: −0.2% [1-sided 95% confidence interval (CI): −8.2%]) on weight loss, physical activity, and hemoglobin A1c compared with a human-led program (Mathioudakis et al., 2025). In addition, a 6-month intervention included a cellular-connected smart scale for daily weighing, web-based weight loss graph, and weekly e-mails with tailored feedback and lessons could lead to 4.04% greater weight loss compared with the control group (Steinberg et al., 2013).

Overall, intensive behavioral interventions can lead to 4%–9% weight loss at 1 year and 1%–3% at 5–10 years (Ahern et al., 2017). However, weight regain after treatment cessation is a common challenge. The DPP study with a follow-up of 10 years demonstrated that, after an initial average loss of 7 kg at 1 year in the intensive lifestyle arm, participants experienced a gradual weight regain, ultimately stabilizing at ~2 kg below baseline (Knowler et al., 2009).

Nutrition

Nutrition interventions play an important role in creating the necessary energy deficit to promote 3%–10% weight loss over 6–12 months (Lingvay et al., 2024). Evidence-based healthy eating approaches can be selected based on individual preference, metabolic risk profile, and likelihood of long-term adherence (Garvey et al., 2016; American Diabetes Association Professional Practice Committee, 2025). Nutrition intervention typically includes calorie restriction, macronutrient adjustments, and time-restricted eating (TRE). Calorie restriction remains the most widely-adopted strategy, which can be implemented through structured diet plans, meal replacements and so on. In addition, a growing body of research suggests that TRE, which limits all calorie intake to specific windows during the day, may provide benefits, particularly for metabolic health. However, its superiority over traditional calorie restriction remains debated. Some studies have reported greater weight loss or metabolic improvements with TRE compared with conventional calorie restriction, whereas others have indicated no additional benefit (Lowe et al., 2020; Liu et al., 2022; Pavlou et al., 2023; Wei et al., 2023; Li et al., 2024a; Maruthur et al., 2024). Interestingly, a randomized, controlled trial including 21 participants demonstrated that, combining TRE with concurrent exercise training could help to reduce 5.7% fat mass and increase 1.3% lean mass in adults with overweight and obesity compared with calorie restriction plus exercise after an 8-week intervention (Kotarsky et al., 2021). Together, current evidence suggests that TRE, particularly when combined with lifestyle interventions such as exercise, may confer additional benefits for body composition and metabolic health, although long-term efficacy and superiority over traditional calorie restriction remain uncertain.

Regardless of the specific nutritional strategies employed, long-term maintenance of weight loss remains a major challenge. It has been reported that high protein intake may have a significant effect on the prevention of weight regain (standardized mean difference: −0.17 [95% CI: −0.29, −0.05]), but this remains to be validated in future randomized clinical trials (van Baak and Mariman, 2019).

Physical activity

Given its modest effect on weight loss (mean effect of −2 kg to −3 kg), physical activity is not used as a stand-alone treatment but may help to sustain weight loss and improve cardiometabolic health. Regular aerobic and resistance exercises improve insulin sensitivity, cardiovascular fitness, and body composition, with resistance training particularly effective in preserving lean mass during caloric restriction (Bellicha et al., 2021; Tucker et al., 2022).

Recent attention has been paid to the potential value of high-intensity interval training (HIIT) in weight management. HIIT is characterized by short periods of high-intensity exercise, commonly <1 min, alternating with short periods of less intense recovery. Beyond its potential metabolic advantages from higher intensity, HIIT is also considered a time-saving exercise mode (Wewege et al., 2017). Data from 12 systematic reviews and meta-analyses including 149 trials demonstrated that, when matched for total energy expenditure, HIIT and aerobic training achieved comparable fat and visceral fat loss (Bellicha et al., 2021).

Innovations in digital and AI-assisted exercise technologies may further enhance adherence and personalization. Recently, an adaptive AI-based virtual reality sports system, named REVERIE, was developed to help lose weight. After an 8-week intervention, REVERIE sports intervention reduced fat mass and improved physical fitness, psychological well-being, and sports willingness compared with conventional physical activity (Wang et al., 2025). Such technologies have the potential to offer scalable solutions for improving engagement and long-term weight maintenance.

Evidence on the role of physical activity in preventing long-term weight regain remains mixed. Several observational data have indicated that fat-free mass was a significant predictor of weight regain (Martins et al., 2022a; Li et al., 2024b), while some randomized controlled trials demonstrated no significant difference in weight maintenance between the exercise and control groups (Borg et al., 2002; Hintze et al., 2018). The inconsistency may be due to the long-term adherence, as some participants in the control group might voluntarily choose to become more physically active, while some participants in the exercise group might not be able to adhere to the prescribed exercise, reducing the between-group difference. Moreover, a randomized, placebo-controlled trial including 195 participants revealed that combining exercise and liraglutide improved weight loss maintenance better than either treatment alone after 1-year intervention (Jensen et al., 2024). Thus, physical activity should be regarded not as an isolated therapy but as a part of a comprehensive management strategy to prevent weight regain.

Pharmacotherapy

A variety of anti-obesity medications now available for clinical use can be classified into three groups based on their mechanisms of action: intragastrointestinal medications (e.g. orlistat), centrally acting medications (e.g. phentermine, phentermine-topiramate, and naltrexone-bupropion), and nutrient-stimulated hormone-based medications (e.g. liraglutide, semaglutide, tirzepatide, and mazdutide). Across randomized trials, typical mean weight loss at 1 year is ~4% with orlistat (Torgerson et al., 2004), 8.8%–9.3% with 15 mg phentermine/92 mg topiramate (Gadde et al., 2011; Allison et al., 2012), 4.8%–5.2% with 32 mg naltrexone/360 mg bupropion (Greenway et al., 2010; Apovian et al., 2013), and 6% with 3.0 mg liraglutide (Davies et al., 2015). Newer nutrient-stimulated hormone-based medications produce larger and more consistent loss and have become the first‑line pharmacotherapy in guidelines (American Diabetes Association Professional Practice Committee, 2025).

Semaglutide is a GLP-1 analog. The randomized, controlled trial including adults with overweight or obesity without diabetes showed that body weight loss in the 2.4 mg semaglutide group was 14.9% at 68 weeks in the STEP 1 trial (Wilding et al., 2021) and 15.2% at 104 weeks in the STEP 5 trial (Garvey et al., 2022). Importantly, in the SELECT cardiovascular outcomes trial of 17604 adults with established atherosclerotic disease and no diabetes, 2.4 mg semaglutide reduced the risk of major adverse cardiovascular events by 20% compared with placebo after 34.2 months of follow-up (Lincoff et al., 2023). Gastrointestinal disorders (typically nausea, diarrhea, vomiting, and constipation) are the most frequently reported events. Most gastrointestinal events are mild to moderate in severity, transient, and resolved without permanent discontinuation of the regimen (Wilding et al., 2021; Garvey et al., 2022).

Tirzepatide is a GIP/GLP-1 receptor agonist. In the SURMOUNT-1 trial, after a 72-week intervention, the mean weight loss was 15.0%, 19.5%, 20.9%, and 3.1% with weekly 5 mg, 10 mg, and 15 mg tirzepatide and placebo, respectively (Jastreboff et al., 2022). In recent phase 3b, open-label, controlled trial, participants with obesity but without type 2 diabetes were randomly assigned to receive the maximum tolerated dose of tirzepatide (10 mg or 15 mg) or the maximum tolerated dose of semaglutide (1.7 mg or 2.4 mg) subcutaneously once weekly for 72 weeks, and the weight loss at 72 weeks was 20.2% with tirzepatide and 13.7% with semaglutide (Aronne et al., 2025). Tirzepatide has a similar adverse event profile, with gastrointestinal symptoms (nausea, diarrhea, vomiting, and constipation) being most frequent. The gastrointestinal symptoms are usually transient and mild to moderate in severity, occurring primarily during the dose-escalation period (Jastreboff et al., 2022).

Mazdutide, a synthetic peptide analog of mammalian oxyntomodulin, is a dual GLP-1 and glucagon receptor agonist. In the 48-week phase 3 GLORY-1 trial, participants with overweight or obesity assigned to once-weekly 4 mg or 6 mg mazdutide achieved mean weight loss of 12.0% and 14.8%, respectively, compared to 0.5% weight loss with placebo (Ji et al., 2025). Beyond weight loss, this agent was also shown to reduce liver fat content and improve glycemic control (Zhang et al., 2024; Ji et al., 2025). The predominant adverse event is gastrointestinal disorder (nausea, diarrhea, decreased appetite, and vomiting) and generally mild to moderate, with a low rate of treatment discontinuation (Ji et al., 2025).

Moreover, AI-assisted peptide discovery is accelerating the development of novel anti-obesity drugs. Using computational drug discovery to systematically predict proteolytic peptide fragments, Coassolo et al. (2025) identified a 12-amino-acid BRINP2-related peptide that reduced food intake without inducing nausea or aversion in mice and pigs.

Weight regain typically occurs when treatment is discontinued. It is reported that >60% of those in the United States who are taking a drug of this class, known as GLP-1 agonists, have stopped using them within 1 year (Prillaman, 2024). Randomized withdrawal studies of anti-obesity medications have consistently shown significant weight regain with therapy cessation. In the STEP 1 trial extension, participants received 68 weeks of once-weekly 2.4 mg semaglutide or lifestyle intervention. At Week 68, treatments (including lifestyle intervention) were discontinued. The study demonstrated that following treatment withdrawal, semaglutide and placebo participants regained 11.6% and 1.9% of lost weight by Week 120, respectively (Wilding et al., 2022). Similarly, the SURMOUNT-4 trial was a phase 3 randomized withdrawal study with a 36-week, open-label tirzepatide lead-in period followed by a 52-week, double-blind, placebo-controlled period. At Week 88, participants receiving tirzepatide maintained >80% weight loss from the lead-in period compared with 16.6% in those transitioned to placebo (Aronne et al., 2024). For mazdutide, no randomized withdrawal studies have been published to date. Beyond weight, metabolic parameters show heterogeneity after discontinuation. Some returned to untreated levels (Wilding et al., 2022), while others partially rebounded, maintaining a net improvement over baseline (Rubino et al., 2021; Aronne et al., 2024). Until now, long-term (>5 years) post-cessation data in pharmacotherapy trials remain limited.

Bariatric procedures

Bariatric procedures remain the most effective intervention for achieving substantial weight loss and improving metabolic health (Chaiyasoot et al., 2023; Perdomo et al., 2023). Beyond metabolic improvement, bariatric procedures are also cost-effective, leading to an incremental cost‑utility ratio of 19359 US dollars per quality-adjusted life years compared to conventional medical management, which was lower than a willingness-to-pay of 20277 US dollars per quality-adjusted life years (Tu et al., 2019). The two most common procedures performed are the sleeve gastrectomy (SG) and the Roux-en-Y gastric bypass (RYGB), and the expected 12-month total weight loss is 25% with meaningful improvements in glycemia, blood pressure, and lipid levels (Tu et al., 2021). In a prospective multicenter observational study of patients with obesity and type 2 diabetes, both SG and RYGB had substantial weight loss at 5 years (%TWL: −20.6% for SG and −20.8% for RYGB), accompanied by significant improvements in glucose control, hepatic steatosis, and cardiovascular risk factors (Bao et al., 2025). Similar results were shown in previous studies (Arterburn et al., 2020). However, a large study including 65093 patients reported that RYGB could achieve a greater weight loss than SG over 5 years (%TWL: −25.5% for RYGB and −18.8% for SG) (Arterburn et al., 2018).

Common adverse events include deficiencies in iron, vitamin D, and vitamin B12, incision site pain, anemia, and vomiting (Yu et al., 2016b). Nutrition deficiencies are more likely with RYGB than with SG, but micronutrient supplementation and monitoring are recommended for all patients (Bal et al., 2012; Yanovski and Yanovski, 2024).

Despite its general efficacy, bariatric surgery is not uniformly effective in all patients. It is well established that a large proportion of patients experience weight regain during the long-term follow-up. In a large prospective cohort study of 1406 adults who underwent RYGB, average weight regain (using percentage of nadir weight) was 5.7% at 1 year after reaching the nadir weight and continued to increase throughout follow-up (2 years: 10.1%; 3 years: 12.9%; 4 years: 14.2%; 5 years: 15%) (King et al., 2018). In another study consisting of 300 participants who underwent RYGB, 37% participants had significant weight regain after a 7-year follow-up using the definition of ≥25% increase from nadir weight (Cooper et al., 2015). A systematic review (Karmali et al., 2013) reported that the estimated prevalence of weight regain ranged from 19% to 87% due to heterogeneity in definitions, thresholds, and follow-up intervals. Thus, it seems that weight regain after bariatric surgery is common, but standardized definitions and long-term management are essential to identify and address clinically significant regain.

The metrics and definition of weight regain

Treatment success should not only be defined by weight loss alone but also capture metabolic health, mental well-being, and quality of life. However, inconsistent definitions and measurements of weight regain impede interpretation of its clinical significance and comparisons across studies (Table 1). To address this gap, several studies have compared the performance of these metrics for clinical outcomes. Lauti et al. (2017) reported significant associations between different definitions of weight regain and the Bariatric Analysis Reporting Outcome System (BAROS) score in 55 patients at 5 years after SG. However, this study did not explore the optimal metrics for weight regain. In a prospective cohort study of 1406 adults who underwent RYGB with a median follow-up of 6.6 years, the percentage of maximum weight lost (%MWL) had the strongest association with most clinical outcomes (diabetes, declines in physical and mental health-related quality of life, and satisfaction with surgery) and ranked second for hyperlipidemia and hypertension (King et al., 2018). A 20% regain in %MWL emerged as the optimal threshold for identifying clinically significant weight regain. Similarly, a retrospective cohort study of 249 participants with obesity and type 2 diabetes reported that %MWL had the highest predictive performance for 3-year postoperative glucose metabolism deterioration compared with weight change, body mass index (BMI) change, percentage of presurgery weight (%PSW), or percentage of nadir weight (%NW). Again, a 20% threshold offered the best discrimination (Si et al., 2023).

Table 1.

Definition and cutoff points of weight regain.

Metric	Definition	Cutoff point
Weight	Any weight regain	0 kg (Jiménez et al., 2012)
BMI	Increase to BMI >  35 kg/m2 after successful weight loss	35 kg/m2 (Carmeli et al., 2015)
ΔWeight	Weight after NW − NW	10  kg (Voorwinde et al., 2020)
ΔBMI	BMI after NW − nadir BMI	5  kg/m² (Lauti et al., 2017)
%PSW	(Weight after NW − NW)/presurgery weight × 100%	10% (King et al., 2018), 15% (Voorwinde et al., 2020)
%NW	(Weight after NW − NW)/NW × 100%	10% (da Silva et al., 2016), 15% (Jiménez et al., 2012; Bastos et al., 2013; Amundsen et al., 2017)
%MWL	(Weight after NW − NW)/(presurgery weight − NW) × 100%	10% (Roslin et al., 2011), 20% (Yanos et al., 2015; King et al., 2018), 25% (Si et al., 2023)
%EWL	(Presurgery BMI − BMI after NW)/(presurgery BMI − 25) × 100%	25% (Homan et al., 2015; Liu et al., 2015)

BMI, body mass index; NW, nadir weight; %PSW, percentage of presurgery weight; %NW, percentage of nadir weight; %MWL, percentage of maximum weight lost; and %EWL, percentage of excess weight loss.

Collectively, these findings support %MWL as a promising metric for predicting long-term weight regain. Nevertheless, comparisons across studies are hampered by heterogeneity in surgery type, follow-up duration, and participants’ baseline characteristics. Further exploration of the associations between different definitions of weight regain and clinical outcomes is needed to develop a standardized, outcome-oriented definition and evidence-based cutoff points.

Predictors of weight regain

Demographic and clinical characteristics

Identifying demographic and clinical factors associated with weight regain may help to identify high-risk patients and guide early intervention. A retrospective study including 1426 patients who underwent RYGB with at least 2 years of follow-up demonstrated that advanced age was a significant predictor of weight regain (Shantavasinkul et al., 2016). Similarly, another study observed a higher proportion of weight regain in older adults over a 60-month follow-up period (Barhouch et al., 2010). Although advanced age is associated with higher complication rates, its negative impact on weight outcomes may be compensated by improvements in comorbidities, and therefore age alone should not preclude consideration for surgical treatment. BMI is one of the most consistently reported predictors of weight regain. Patients with higher initial BMI tend to achieve greater absolute weight loss (Obeidat and Shanti, 2016; Cottam et al., 2017, 2019; Steinbeisser et al., 2017; Janse Van Vuuren et al., 2018).

Moreover, some clinical characteristics may impact the efficacy of weight loss. Several studies have reported that patients with type 2 diabetes at baseline are more likely to undergo weight regain after bariatric surgery (Ortega et al., 2012; Goldenshluger et al., 2017; Courcoulas et al., 2018). A retrospective study of 187 patients with obesity and type 2 diabetes who underwent RYGB showed that hemoglobin A1c was an independent predictor of weight regain after 3 years of follow-up (Si et al., 2025). The area under curve of the nomogram constructed from variables including hemoglobin A1c was 0.781. Therefore, it is important to understand the relationship between type 2 diabetes and weight regain, although a direct association has not yet been established.

Behavioral factors

Increasing studies have focused on the importance of behaviors in determining weight loss stability. Behavioral factors can be summarized into three categories: self-monitoring, energy intake, and energy expenditure.

In terms of self-monitoring, the Longitudinal Assessment of Bariatric Surgery-2 (LABS-2) study is a multicenter observational cohort study at 10 US hospitals in six geographically diverse clinical centers. The study demonstrated that the mean weight change was −33.9% among those in the weekly self-weighing group and −31.0% among those who never engaged in this behavior (Mitchell et al., 2016). Moreover, weekly self-weighing, not continuing to eat when full, and not eating continuously during the day explained 16% of the variability in 3-year weight change after RYGB. Self-monitoring of physical activity was also shown to have moderate effect on predicting weight loss maintenance (Varkevisser et al., 2019).

Regarding behaviors associated with energy intake, several eating behaviors are associated with weight regain. It was reported that ‘stopping eating when full’ was associated with −33.9% mean loss at 3 years vs. −24.7% in those who always continued to eat when full; stopping ‘eating continuously during the day’ was associated with −34.8% vs. −29.2% when this behavior persisted (Mitchell et al., 2016). Moreover, eating patterns such as increased fruit and vegetable consumption, reduced fat intake, and decreased sugar-sweetened beverage intake were positively associated with weight loss maintenance (Varkevisser et al., 2019).

For energy expenditure, sustained physical activity helps counter metabolic adaptation and optimize weight loss (Jakicic et al., 2001; Bellicha et al., 2018). A systematic literature review and meta-analysis including 15 studies indicated that structured exercise training yielded an additional 2.4 kg weight loss, 2.7 kg more fat mass loss, improved VO₂ max, and enhanced physical fitness (Bellicha et al., 2018).

Anatomic factors related to bariatric procedures

Postoperative anatomic changes contribute significantly to weight regain. Enlargement of the gastrojejunal stoma after RYGB and dilation of the gastric sleeve after SG reduce mechanical restriction and satiety. Other structural abnormalities, such as hiatal hernia or gastric leak, may further diminish weight-control efficacy (Abu Dayyeh et al., 2011; Athanasiadis et al., 2021; Noria et al., 2023). Early detection through endoscopy or imaging enables timely intervention, which included endoscopic suturing or revisional surgery when appropriate.

Biomarkers

Emerging data implicate hormonal and inflammatory biomarkers in weight regain. Serum ghrelin (Tamboli et al., 2014), cortisol (Casteràs et al., 2024), and interleukin 6 level (Qiao et al., 2022) were positively associated with, while serum GLP-1 (Santo et al., 2016), fibroblast growth factor 21, growth differentiation factor 15 (Fiorenza et al., 2024), and vitamin D levels (Aladel et al., 2022) were negatively associated with weight regain. These associations remain observational, and prospective validation is needed before routine clinical use.

Physiological mechanisms underlying weight regain after intentional weight loss

Intentional weight loss elicits coordinated biological responses that defend against further loss and favor weight regain. These adaptations include adipose-tissue biology, metabolic adaptation, and gut hormone.

Obesity memory

It is reported that weight loss does not fully reverse obesity-related changes within the adipose tissue. Zou et al. (2018) developed a weight gain–loss–regain model and found that C57BL/6J mice on a high-fat diet regained body weight much faster than those did not experience the weight cycle. Notably, even after 2 months, the phenomenon still persisted. Mechanistically, the study revealed that immune cells, especially CD4+ T cells, played an important role in this process, and depletion of CD4+ T cells abolished the obesity memory (Zou et al., 2018). Subsequent work using cellular indexing of transcriptomes and epitopes by sequencing in male mice further supported this phenomenon. The study reported that obesity-induced imprinting of adipose tissue immune cells persisted after weight loss and worsened with subsequent weight regain, resulting in impaired restoration of type 2 regulatory cells, activation of antigen-presenting cells, T-cell exhaustion, and enhanced lipid handling by macrophages during weight cycling (Cottam et al., 2022).

In humans, a randomized controlled trial included 61 participants with overweight or obesity who followed either a 5-week very-low-calorie diet (500 kcal/day) or a 12-week low-calorie diet (1250 kcal/day) with a subsequent 4-week weight stabilization phase and a 9-month follow-up. Subcutaneous adipose-tissue biopsies taken before and after the diet intervention were subjected to microarray analyses focusing on 277 genes implicated in extracellular matrix (ECM) remodeling and leukocyte integrin signaling. Of these genes, 26 showed significant correlations with the percentage of weight regain, and four genes (ITGAX, ITGAM, ITGAX, and ITGB2) coded for leukocyte-specific receptors, highlighting a critical role of adipose tissue immune cell interactions with ECM pathways in weight-regain risk (Roumans et al., 2017). Further evidence came from paired adipose-tissue biopsy in humans undergoing bariatric surgery and healthy control. Despite substantial weight loss, adipocytes, adipose precursor cells, and endothelial cells retained obesity-induced gene-expression changes. Specifically, ~40%–50% of the differentially expressed genes associated with obesity in adipocytes remained deregulated during the 2-year follow-up compared with lean controls. These changes were enriched in pathways related to lipid metabolism, ECM remodeling, and immune-cell recruitment. The study further used murine models and demonstrated that many promoters and enhancers, marked by the active transcription start site marker H3K4me3 and the inhibitory histone modification marker H3K27me3, persisted after weight loss and primed the adipose tissue for exaggerated expansion when re-exposed to a high-fat diet (Hinte et al., 2024).

Collectively, these findings establish that obesity induces durable cellular, transcriptional, and epigenetic changes within the adipose tissue and its immune microenvironment. ‘Obesity memory’ may represent a biological substrate for weight regain after successful loss. Understanding and targeting these molecular pathways through anti-inflammatory, immunomodulatory, or epigenetic therapies may provide new strategies for preventing weight regain and achieving sustained weight control.

Metabolic adaptation

Metabolic adaptation, also known as adaptive thermogenesis, is a phenomenon that resting energy expenditure and total energy expenditure decline more than expected from changes in fat mass and fat-free mass (Leibel et al., 1995). A study included 16 subjects who underwent a weight-loss program consisting of diet restriction and vigorous exercise to preserve fat-free mass and maintain resting metabolic rate (RMR). After a 30-week intervention, RMR declined disproportionately to the decrease in BMI (−244 ± 231 kcal/day at Week 6 and −504 ± 171 kcal/day at Week 30), demonstrating substantial metabolic adaptation (Johannsen et al., 2012). Another study of 65 overweight women who followed an 800-kcal/day diet until BMI ≤25 kg/m² demonstrated that metabolic adaptation at weight stability averaged −46 ± 113 kcal/day, and each additional 10  kcal/day of adaptation lengthened the time to reach the weight-loss goal by ~1 day (Martins et al., 2022b). Metabolic adaptation has also been observed after bariatric surgery (Knuth et al., 2014; Bettini et al., 2018).

However, it is still controversial whether metabolic adaptation persists after energy balance is restored and BMI is stable. Some studies have reported that metabolic adaptation disappeared once energy balance was restored, while others suggested that it was maintained. Fothergill et al. (2016) demonstrated that although a large proportion of lost weight was regained, the RMR was still below baseline in 14 participants of ‘The Biggest Loser’ competition. In contrast, Martins et al. (2020) indicated that metabolic adaptation was not associated with weight regain during 2 years of follow-up in 171 women with overweight who underwent lifestyle intervention. The discrepancies may be related to the differences in the intervention, the definition of metabolic adaptation, and amount of weight loss and regain in these studies. More data regarding the maintenance of metabolic adaptation in the long term after weight loss are required.

Gut hormones

The gut, often described as the body’s largest endocrine organ, secretes >20 polypeptide hormones in response to nutrient exposure, collectively termed as gut hormones (Koliaki et al., 2020). These hormones are central to the regulation of appetite, satiety, energy balance, and glucose homeostasis and implicated in the pathogenesis of obesity.

A systematic review and meta-analysis (Aukan et al., 2023) reported that individuals with obesity had significantly lower fasting and postprandial ghrelin and peptide YY (PYY) concentrations compared with those of normal weight, although no consistent differences were observed for GLP-1, cholecystokinin, or other appetite-related hormones. Notably, substantial heterogeneity across studies highlights the dynamic and complexity of gut-hormone secretion. Increasing studies suggested that weight loss induced by diet and bariatric surgery had different impacts on circulating gut hormone levels (Shiiya et al., 2002; Manell et al., 2016; Zhao et al., 2017; Koliaki et al., 2020). For example, PYY decreased after a 10-week very-low-energy diet but increased after SG (Sumithran et al., 2011; McCarty et al., 2020). However, the role of circulating gut hormone before and after a meal as biomarkers of weight changes or regain has not been fully elucidated.

Emerging studies also implicate the gut–brain axis in regulating food reward and appetite following weight loss. An observational study reported that SG induced functional changes in the right putamen and left supplementary motor area. These neural changes correlated well with alterations in the relative abundance of Clostridia, as well as postprandial levels of GLP-1 and ghrelin (Hong et al., 2021). Similar findings were seen in several studies (Batterham et al., 2007; Makaronidis and Batterham, 2018). In summary, gut hormones influence weight regulation through both peripheral metabolic effects and central appetite control. Further research integrating hormonal, microbial, and neuroimaging data may help clarify how these systems interact to prevent weight regain after successful weight loss.

Future perspectives

The future of weight management requires shifts from episodic weight loss to continuous, long-term health maintenance. This transition will be driven by several critical advances (Figure 2). First, standardized, clinically meaningful metrics for weight regain should be established to uniformly evaluate outcomes across trials and practice. Second, therapeutic strategies must evolve to encompass not only next-generation pharmacotherapy but also novel options like targeted drug delivery systems, gut microbiome modulation, and evidence-based gene therapies. Third, developing AI-driven tools can help to stratify risk, offer personalized treatment, and support adherence. Finally, these innovations must be embedded into clinical practice and ethical frameworks to ensure equitable access and long-term cost-effectiveness, making weight management a sustainable reality for health system.

Figure 2.

The future of long-term weight management.

Funding

The study was supported by grants from the Noncommunicable Chronic Diseases—National Science and Technology Major Project (2023ZD0509200 and 2023ZD0509201), Shanghai Research Center for Endocrine and Metabolic Diseases (2022ZZ01002), and the National Key Clinical Specialty (Z155080000004).

Conflict of interest: none declared.