What this is
- Obesity results from complex interactions between genetic predispositions and environmental factors.
- This review contrasts , caused by mutations in single genes, with , influenced by numerous genetic variants.
- It discusses key genes and signaling pathways involved in obesity, highlighting the role of genetic insights in developing precision pharmacotherapy.
Essence
- Obesity arises from both rare monogenic mutations and common polygenic variants, each influencing energy regulation and appetite. Advances in pharmacotherapy, particularly GLP-1 receptor agonists, show efficacy across diverse genetic backgrounds.
Key takeaways
- stems from rare mutations in key genes like LEP and MC4R, leading to severe early-onset obesity. These mutations disrupt neuroendocrine signaling pathways that regulate appetite and energy balance.
- involves over 1,100 genetic loci, each contributing a small effect to obesity risk. Polygenic risk scores can predict individual susceptibility and guide personalized prevention strategies.
- Recent pharmacological advancements, including GLP-1 receptor agonists, demonstrate significant weight loss irrespective of genetic background, suggesting broad applicability for diverse patient populations.
Caveats
- The integration of genetic testing into clinical practice faces challenges related to cost and complexity. Not all variants are well understood, which may limit their utility in treatment decisions.
- While polygenic risk scores are promising, they require validation across diverse populations to ensure their effectiveness in predicting obesity risk.
Definitions
- Monogenic obesity: Obesity caused by rare mutations in a single gene, resulting in severe and early-onset phenotypes.
- Polygenic obesity: Obesity arising from the cumulative effects of numerous common genetic variants, each contributing a small increase in risk.
- Polygenic risk score (PRS): A score that aggregates the effects of multiple genetic variants to estimate an individual's risk of developing obesity.
Simplified
Introduction
Obesity as a clinical condition is becoming a growing problem according to data from the World Health Organization (WHO). According to the WHO, around 2.5 billion adults were overweight in 2022, and 890 million of these were obese).1 The main factor contributing to obesity is the consumption of high-calorie foods, but other factors also play a role and sometimes even have a decisive influence, such as endocrine dysfunction, genetics, and sleep (Keith et al., 2006). Obesity is associated with multiple comorbidities, including various diseases such as cardiovascular disease (Singh et al., 2013), type 2 diabetes (Singh et al., 2013), non-alcoholic fatty liver disease (Li et al., 2016), and high blood pressure (Wang and Wang, 2004). It has been reported that obesity can double the risk of high blood pressure and triple the risk of type 2 diabetes (DMT2) (Thompson et al., 1999). Environmental factors are certainly involved in the rapid increase in prevalence, which results from the interaction of environmental factors and innate biological factors. There are significant genetic factors involved in body weight variation that determine the response to obesogenic environmental factors. For example, twin studies have estimated the heritability of obesity to be between 40% and 70% (Elks et al., 2012; Loos and Yeo, 2022; Lister et al., 2023).
Following established traditional protocols, Loos and Yeo (2022) divided obesity into two categories. First, there is monogenic obesity, which is based on Mendelian rules associated with a severe disease course and states that underlying mechanisms of obesity would include deletions in the chromosome or the deletion of a single gene Second, there is polygenic obesity, also known as common obesity, which is associated with hundreds of polymorphisms (Loos and Yeo, 2022).
Polygenic obesity, the most common form of obesity, is caused by the additive effects of numerous common genetic variants—current studies identify over 500 loci that contribute to a small extent to interindividual differences in body mass index and fat mass (Loos, 2025; Smit et al., 2025). In contrast to rare monogenic obesity, polygenic obesity involves the cumulative influence of alleles with low penetrance in genes involved in appetite regulation (such as FTO and MC4R), energy homeostasis, and adipogenesis (Van Uhm et al., 2025). Genome-wide association studies (GWAS) have shown that these variants interact strongly with environmental influences such as diet, physical activity, and socioeconomic status to influence obesity risk (Loos, 2025; Van Uhm et al., 2025). Polygenic risk scores validated in a recent cohort enable the quantification of individual genetic susceptibility and the prediction of obesity in populations studies (Masip et al., 2025; Menon et al., 2024; Saeed et al., 2025). These scores underscore the need to combine genetic stratification with personalized lifestyle. Healthy environmental changes can themselves reduce the genetic risk for obesity, while unfavorable conditions can exacerbate this risk (Van Uhm et al., 2025).
Consanguinity, defined as the connection between individuals who are genetically closely related (Temaj et al., 2022), increases the likelihood of homozygosity for rare pathogenic variants and thus the risk of monogenic forms of obesity, such as those caused by mutations in the LEP (leptin) or LEPR (leptin receptor) genes. This genetic factor is particularly significant in populations with a high rate of consanguineous marriages, where the probability of mutation of recessive features increases significantly. Population studies have indicated that mutations in genes such as LEP, LEPR, and MC4R may explain up to 30% of cases of severe early-onset obesity. Mutations in LEP and LEPR follow an autosomal recessive inheritance pattern, leading to extreme, rapid-onset obesity and hyperphagia; these cases are often associated with metabolic and hormonal disorders. The finding of new mutations in the LEPR gene in consanguineous families underlines the value of genetic screening in this context, where the clinical feature typically corresponds to leptin deficiency; severe early-onset obesity, intense hyperphagia, and hypogonadal hypogonadism is also possible in these cases (Chaves et al., 2022; Dayal et al., 2018; Niazi et al., 2018).
Genetic research studies on monogenic and polygenic obesity have shown that the underlying biology is based on common neuroendocrine signaling pathways that primarily affect the central regulation of appetite and energy balance of the brain. Loos and Yeo (2022) point out that genes first associated with rare, severe, early-onset monogenic obesity—such as LEP, LEPR, POMC, and MC4R—repeatedly share variants that influence body mass index in the general population, suggesting a key role for the hypothalamic leptin-melanocortin signaling pathway in both forms of obesity (Loos, 2025; Loos and Yeo, 2022). Similarly, Trang and Grant (2023) note that genes originally discovered in monogenic contexts, including MC4R and POMC, overlap with loci identified in large-scale polygenic studies and act via common biological signaling pathways such as BDNF–TrkB (Brain-Derived Neurotrophic Factor–Tropomyosin Receptor Kinase B) and leptin–melanocortin (Trang and Grant, 2023). Hinney et al. (2010) further emphasize that while rare mutations in monogenic obesity cause dramatic phenotypes, the same biological pathways are modulated more subtly by numerous common variants in polygenic obesity, supporting the notion that both genetic architectures ultimately converge on largely similar neural mechanisms for regulating energy homeostasis (Hinney et al., 2010). In this review, we summarize genetic studies that have characterized molecules and mechanisms as well as therapies for controlling body weight.
The leptin-melanocortin signaling pathway: central mechanisms regulating appetite and energy homeostasis in obesity
The leptin-melanocortin signaling pathway plays a crucial role in biochemical signaling pathway-related obesity by regulating appetite and energy homeostasis. It is known that leptin is secreted by adipose tissue, binds to leptin receptors (LEPR) in the hypothalamus, and activates intracellular signaling cascades, such as the JAK-STAT and PI3K signaling pathways, to regulate neuronal activity. This process stimulates pro-opiomelanocortin (POMC) neurons to produce α- and β-melanocyte-stimulating hormones (MSH), which subsequently activate melanocortin-4 receptors (MC4R) to produce satiety signals that suppress appetite and increase energy expenditure. At the same time, leptin can inhibit agouti-related peptide (AgRP) neurons and counteract MC4R signaling, thus reducing appetite. Disruptions in any of the components of this signaling pathway, such as mutations in LEP, LEPR, POMC, or MC4R, often lead to severe early-onset obesity because they impair these regulatory mechanisms. The role of this pathway in energy balance is confirmed by clinical studies showing altered protein levels of pathway components in obese patients, as well as by experimental models in which loss of function leads to increased food intake and weight gain (Collet and Schwitzgebel, 2024; Farooqi, 2023; Tas et al., 2022; Yeo et al., 2021). Maintaining the integrity of this signaling pathway is crucial for controlling body weight and represents an important target for obesity therapy (Figure 1).
This schematic illustrates the central leptin-melanocortin pathway regulating appetite and energy homeostasis, with monogenic obesity genes positioned along the signaling cascade.
Gene discovery in obesity
Gene discovery in monogenic obesity
The discovery of genes for monogenic obesity began with the identification of rare, highly penetrant mutations that lead to severe early-onset obesity, particularly in genes of the leptin-melanocortin signaling pathway such as LEP, LEPR, POMC, and MC4R (Loos, 2025). Targeted panels for the 25–35 genes listed here (including LEP, LEPR, MC4R, POMC, PCSK1, SIM1, and SH2B1) using NGS show a diagnostic yield of approximately 5%–7% in severe early-onset cohorts (Künzel et al., 2025). Based on the guidelines from ACMG/AMP (Richards et al., 2015), variants should be classified into five categories: Pathogenic (P), Likely Pathogenic (LP), Variant of Uncertain Significance (VUS), Likely Benign (LB), or Benign (B) (Richards et al., 2015). These genes were initially characterized in affected humans and corresponding animal models, demonstrating their central role in appetite regulation and energy homeostasis (Mohammed et al., 2023; Saeed et al., 2023). The leptin-melanocortin pathway is fundamental for maintaining energy homeostasis, as it governs both appetite regulation and overall energy balance within the body. The most commonly affected gene is MC4R (melanocortin 4 receptor), whose mutations are the main cause of non-syndromic severe early-onset obesity and account for up to 6% of cases of severe obesity (Künzel et al., 2025). Other important genes are LEP (leptin) and LEPR (leptin receptor) (Chung, 2012; Nunziata et al., 2019). The genes listed below POMC (pro-opiomelanocortin) (Huvenne et al., 2016) are PCSK1, SIM1, NTRK2, and those encoding proteins associated with Bardet-Biedl syndrome (BBS) (Huvenne et al., 2016; Künzel et al., 2025). The rare deletion in chromosomes, such as the 16p11.2 microdeletion, which includes the SH2B1 gene, are also associated with obesity (Künzel et al., 2025). Taking all of this information together, it is clear these genes underscore the critical role of neuroendocrine circuits in controlling body weight, with monogenic obesity representing severe phenotypes caused by defects in a single gene (Figure 2) (Huvenne et al., 2016; Künzel et al., 2025). Table 1 lists the rare, highly penetrant mutations in important neuroendocrine circuits that primarily affect the leptin-melanocortin signaling pathway and cause severe phenotypes of monogenic obesity.
This figure clarifies the main categorical distinction.
| Gene | Full name | Pathway/function | Typical phenotype | References |
|---|---|---|---|---|
| LEP | Leptin | Leptin-melanocortin; appetite regulation | Severe early-onset obesity, hyperphagia, endocrine effects | [Mohammed et al. (2023)] |
| LEPR | Leptin receptor | Leptin-melanocortin; appetite regulation | Severe early-onset obesity, metabolic disturbances | ,, [Nunziata et al. (2019)] [Chaves et al. (2022)] [Mohammed et al. (2023)] |
| POMC | Pro-opiomelanocortin | Leptin-melanocortin; precursor hormone | Severe early-onset obesity, adrenal insufficiency | , [Krude et al. (1998)] [Mendiratta et al. (2011)] |
| MC4R | Melanocortin 4 receptor | Leptin-melanocortin; appetite regulation | Most common, severe non-syndromic early-onset obesity | [Sridhar and Gumpeny (2024)] |
| PCSK1 | Proprotein convertase subtilisin/Kexin type 1 | Hormone processing | Severe early-onset obesity, hormonal deficiencies | , [Ramos-Molina et al. (2016)] [Stijnen et al. (2016)] |
| SIM1 | Single-minded family bHLH transcription factor 1 | Hypothalamic development | Severe obesity, sometimes associated with neurobehavioral disorders | , [Jr (2000)] [Mohammed et al. (2023)] |
| NTRK2 | Neurotrophic receptor tyrosine kinase 2 | BDNF signaling; appetite regulation | Severe obesity, neurodevelopmental symptoms | , [Gray et al. (2007)] [Alhamas et al. (2022)] |
| SH2B1 1 | SH2B adaptor protein 1 | Leptin/melanocortin & insulin signaling | Obesity with insulin resistance (often due to 16p11.2 deletion) | , [Perrone et al. (2010)] [Hanssen et al. (2023)] |
| genes BBS 2 | Bardet-biedl syndrome gene family | Ciliopathy; various cellular functions | Syndromic obesity, cognitive impairment, retinal dystrophy | [Guo and Rahmouni (2011)] |
LEP gene
Mutations in the LEP gene, which is responsible for encoding the hormone leptin, are a rare but well-documented cause of severe early-onset obesity in humans. Patients with congenital leptin deficiency due to homozygous or heterozygous LEP mutations display rapid and uncontrolled weight gain in early childhood, often followed by serious hyperphagia and significant metabolic disorders. Many clinical studies have reported that such mutations impair leptin production or function, disrupting hypothalamic regulation of appetite and satiety and leading to profound changes in energy balance and obesity. Patients with LEP gene mutations typically have low or undetectable levels of leptin in serum and may develop complications such as metabolic syndrome, fatty liver disease, or hypogonadism (Strobel et al., 1998; Fischer-Posovszky et al., 2010; Yupanqui-Lozno et al., 2019). It is notable that leptin replacement therapy in these patients can effectively reduce food intake, normalize body weight, and correct associated metabolic disorders, underscoring the central role of the LEP gene in human energy homeostasis (Dayal et al., 2018; Zhao et al., 2014).
gene LEPR
The mutations in the LEPR gene (which encode the leptin receptor) are known to cause monogenic severe early-onset obesity. Patients with biallelic pathogenic LEPR gene mutations typically manifest marked hyperphagia and fast weight gain beginning in infancy or early childhood. These types of mutation have the ability to disrupt the binding or signal transduction function of the leptin receptor and cause leptin resistance; although the presence of leptin is higher in the blood, the appetite-regulating pathways in the hypothalamus do not respond to the satiety signal, resulting in uncontrolled food intake and severe obesity. Other clinical features which are shown to be commonly associated with LEPR deficiency include hypogonadotropic hypogonadism and, to varying degrees, changes in pubertal development or hormonal disorders, while metabolic pathway complications such as type 2 diabetes may also occur (Kleinendorst et al., 2020). Recent studies reported that MC4R agonists such as setmelanotide can significantly decrease weight and hunger in patients with confirmed LEPR mutations, underscoring the importance of accurate genetic diagnosis for personalized treatment strategies (Chaves et al., 2022; Nunziata et al., 2019; Supti et al., 2024).
gene POMC
The gene POMC is known to encode pro-opiomelanocortin, and mutations of the POMC gene are shown to cause rare but severe forms of monogenic obesity (Künzel et al., 2025). This type of obesity is characterized by rapid, early-onset weight gain, intense hyperphagia, and pronounced endocrine disorders. Patients with homozygous or heterozygous POMC mutations usually develop severe obesity within the first year of life, as well as secondary adrenal insufficiency due to ACTH (adrenocorticotropic hormone) deficiency and distinctive traits such as pale skin and red hair arise from inadequate levels of melanocyte-stimulating hormones, resulting in reduced melanin production in the hair and skin. These findings underscore the critical role of POMC-derived peptides in regulating many processes in the body such as appetite, energy homeostasis, adrenal function, and pigmentation via the leptin-melanocortin signaling pathway (Yeo et al., 2021). Comprehensive reviews and literature searches often highlight the importance of considering POMC deficiency in cases of severe, early-onset obesity combined with adrenal insufficiency even when characteristic changes in pigmentation are absent, as phenotypic expression can vary widely in individuals with similar genetic mutations (Çetinkaya et al., 2018; Dubern et al., 2008; Mendiratta et al., 2011).
gene MC4R
Gene mutations in MC4R are a common form of monogenic obesity (Giannopoulou et al., 2026) and are characterized by early-onset severe obesity, hyperphagia (increased appetite), and metabolic disorders such as hyperinsulinemia and dyslipidemia. The gene MC4R encodes the melanocortin-4 receptor, a G-protein-coupled receptor that plays a pivotal role in many signaling pathways such as hypothalamic leptin-melanocortin, which is responsible for regulation of energy balance by suppressing food intake and increasing energy expenditure (Imangaliyeva et al., 2025). Both heterozygous and homozygous mutations in the MC4R gene have been documented; patients with homozygous mutations frequently experience a significantly more severe clinical presentation compared to those with heterozygous variants. Individuals with MC4R mutations often show rapid weight gain, impaired satiety, and increased linear growth in infancy or early childhood. The variable penetrance and expressivity of MC4R gene mutations have shown to influence clinical severity, but the primary features remain consistent. Targeted therapies such as the MC4R gene agonist setmelanotide have been reported to offer clinical benefit by reducing hyperphagia and promoting weight loss in affected individuals. Despite great advances, treatment remains multifaceted and includes lifestyle interventions and new pharmacotherapies tailored to genetic diagnosis (Doulla et al., 2014; Imangaliyeva et al., 2025; Sridhar and Gumpeny, 2024; Wade et al., 2021).
gene PCSK1
The PCSK1 gene is responsible for producing the enzyme proprotein convertase 1/3 (PC1/3). Mutations in the PCSK1 gene are responsible for rare but severe forms of monogenic early-onset obesity (Verde et al., 2025). This type of enzyme is crucial for the proteolytic processing of various neuropeptides and prohormones, including those involved in the regulation of appetite, energy balance, and glucose metabolism, such as proopiomelanocortin and proinsulin. The PCSK1 p.Asn221Asp (c.661 A > G) variants have been associated with metabolic pathways, fatty acid oxidation, and hormone processing, increasing the risk of obesity (Verde et al., 2025). Loss-of-function mutations in the PCSK1 gene result in impaired cleavage of these hormone precursors, leading to hyperphagia, severe obesity, and multiple discordance of the endocrinopathies, such as adrenal insufficiency, hypogonadism, and malabsorptive diarrhea in infancy. Both homozygous and heterozygous mutations can cause a spectrum of clinical features, ranging from extreme obesity with neuroendocrine dysfunction to milder phenotypes in heterozygous carriers. These findings underscore the crucial role of PCSK1 in energy homeostasis and endocrine regulation in humans (Löffler et al., 2017; Ramos-Molina et al., 2016; Stijnen et al., 2016).
gene SIM1
SIM1 gene mutations are responsible for rare forms of monogenic obesity (Mohammed et al., 2026), characterized by early-onset severe obesity, hyperphagia, and, frequently, neurological behavioral abnormalities such as developmental delays, intellectual disability, and autism. The SIM1 gene is responsible for encoding a transcription factor which is essential for neuronal development in the paraventricular nucleus of the hypothalamus, a brain region critical for the regulation of appetite and energy balance (Mohammed et al., 2026). Loss-of-function mutations reduce SIM1 transcription activity, leading to hypothalamic dysfunction, increased food intake, and, thus, severe obesity. Some affected individuals show features of Prader-Willi syndrome, such as hypotonia and facial dysmorphia, although this phenotype is variable. Many family studies shave shown that rare SIM1 gene variants contribute significantly to familial obesity risk, with mutation severity and environmental factors influencing phenotypic expression. These findings confirm the central role of SIM1 in neurodevelopment and energy homeostasis and mark it as a key gene for genetic screening in early-onset obesity (Bonnefond et al., 2013; Ramachandrappa et al., 2013; Stanikova et al., 2017).
gene NTRK2
The gene NTRK2 is responsible for the encoding of tropomyosin receptor kinase B (TrkB) (Roussel-Gervais et al., 2023), and mutations in this gene have been associated with severe early-onset obesity characterized by hyperphagia and a disturbed energy balance. The receptor kinase TrkB plays a pivotal role in the brain-derived neurotrophic factor (BDNF) signaling pathway, particularly in hypothalamic neurons that regulate appetite and energy expenditure (Roussel-Gervais et al., 2023). Loss-of-function mutations or deletions of the NTRK2 gene in key hypothalamic regions such as the paraventricular nucleus increase food intake, decrease physical activity, and cause rapid weight gain. Functional studies of human NTRK2 mutations, such as the Y722C variant, show impaired receptor signaling and neuronal function, which may contribute to deficits in hypothalamic neurogenesis and pronounced obesity phenotypes. Furthermore, selective deletion of Ntrk2 in hypothalamic neurons of mice reproduces hyperphagic obesity, underscoring the important role of the NTRK2/TrkB signaling pathway in energy homeostasis (An et al., 2020; Berger et al., 2025). The NTRK2 gene may explain the severe obesity observed in obesity carriers (Köroğlu et al., 2024).
gene SH2B1
SH2B1 encodes an adapter protein that amplifies the signaling pathways of several hormones crucial for energy homeostasis, including leptin and insulin. Mutations in the SH2B1 gene have shown to have a significant impact on obesity, particularly severe early-onset forms characterized by hyperphagia and insulin resistance. Loss-of-function mutations in the SH2B1 gene disrupt the leptin signaling pathway in the hypothalamus, causing impaired regulation of appetite and energy expenditure, which also results in increased food intake and rapid weight gain. In other words, these types of mutations contribute to insulin resistance and type 2 diabetes, further complicating the metabolic profile of affected individuals. Behavioral abnormalities such as social isolation and aggression have also been observed in patients with SH2B1 gene mutations, suggesting a broader role for SH2B1 gene in neurological function. Mouse models with targeted deletion on the gene SH2B1 replicate many human phenotypes, such as hyperphagia, obesity, and glucose intolerance, underscoring the critical regulatory role of the gene in metabolism and energy balance (Chermon and Birk, 2024; Doche et al., 2012; Rui, 2014).
Deletions in chromosome 6q16 (including the SIM1 gene), 11p13 (including the BDNF gene), and distal 16p11.2 (including the SH2B1 gene; OMIM #613444) are associated with obesity. (Chung et al., 2021; D’Angelo et al., 2018; Han et al., 2008; Faivre et al., 2002). A study by da Silva et al., showed the same deletion (three genomic deletions at the 16p11.2) in the same region in patients with severe obesity from Brazil. Based on this report, clinical and genetic testing should be carried out to identify patients with the genetic form of severe obesity. This will support specific medical treatment, genetic counselling, and targeted therapeutic intervention (Da Silva Assis et al., 2025).
BBS-related gene mutations
BBS is a rare autosomal recessive disorder whose main characteristic is obesity. Mutations in several BBS-related genes disrupt the function of the BBSome, a protein complex that is essential for the proper functioning of cilia and that influences energy regulation. Obesity is usually severe and early onset in BBS patients and is often accompanied by hyperphagia and reduced physical activity. Studies in BBS knockout mice, such as those lacking Bbs2, Bbs4, or Bbs6, show increased obesity due to both increased food intake and reduced energy expenditure. It is noteworthy that BBS patients tend to have more visceral fat and altered body composition compared to control subjects with the same BMI. In addition, heterozygous carriers of BBS mutations may have an increased risk of obesity without showing the full syndromal phenotype. These findings show that BBS gene mutations contribute to obesity by impairing central appetite and metabolic regulation via cilia dysfunction, making BBS an important model for understanding syndromic obesity (Benzinou et al., 2006; Guo and Rahmouni, 2011; Li et al., 2024; Zhong et al., 2025).
BBS is a rare autosomal recessive ciliopathy caused by biallelic mutations in 20+ BBS genes (BBS1, BBS2, BBS10, etc.). Disruption of the BBSome-mediated primary cilia function in neurons/adipocytes impairs MC4R trafficking and leptin-melanocortin signaling, causing severe early-onset obesity, hyperphagia, polydactyly, retinitis pigmentosa, and renal/genital anomalies. Mouse models (Bbs2/4/6 KO) confirm hyperphagia + reduced energy expenditure; heterozygous carriers show increased obesity risk without the full syndrome. Setmelanotide is a known MC4R agonist, which bypasses proximal defects by directly activating MC4R. In a phase 3 trial (NCT03746522↗), BBS patients showed significant BMI decreases, hunger suppression, and metabolic improvements, earning FDA approval as a first-targeted therapy for BBS obesity, and a 3-year extension confirmed the sustained benefits (stabilization/improvement in weight and QoL) (Haqq et al., 2025; 2022; Yanovski et al., 2024).
Gene discovery in polygenic obesity
Polygenic obesity results from the additive effects of hundreds to thousands of common genetic variants, each of which confers a small increase in susceptibility to a higher body mass index and obesity (Khera et al., 2019; Loos and Yeo, 2022). GWAS (Genome-Wide Association Study) have reported more than 500 genetic loci associated with enhanced BMI, with the strongest effects observed in variants in genes such as FTO and MC4R, but each variant alone explains only a small fraction of the phenotypic variance (Hinney et al., 2010; Loos and Yeo, 2022). Genes SEC16B and LINC02702 were also identified in GWAS meta-analyses of obesity traits. In total, more than 1,100 loci have been identified in research on polygenic obesity, underscoring the complex genetic architecture of this trait with many variants, each of which has a small effect; neuroendocrine control of appetite and energy homeostasis are regulated by some of them (Figure 2) (Jo et al., 2024; Smit et al., 2025; Van Uhm et al., 2025). To quantify genetic risk, the different research groups aggregated the effects of these variants into polygenic scores, which show that persons with a high cumulative genetic burden have a significantly increased risk of severe obesity—sometimes even on a scale comparable to the influence of rare monogenic mutations (Khera et al., 2019). In spite of this genetic burden, environmental factors and gene-environment interactions remain crucial in determining whether a person with high polygenic risk will actually develop obesity. Polygenic risk scores (PRS) effectively identify individuals at elevated risk for obesity. They enhance the understanding of obesity’s biological mechanisms. PRS also enables the development of personalized prevention strategies (Khera et al., 2019; Loos and Yeo, 2022).
Table 2 illustrates the complex polygenic architecture of obesity, in which each gene makes a small contribution, as well as the importance of interactions between genes and the environment for the phenotype.
| Gene | Full name | Main biological pathway/function | References |
|---|---|---|---|
| FTO | Fat mass and obesity-associated | Regulation of energy intake and adipogenesis | ,, [Hinney et al. (2010)] [Merkestein et al. (2015)] [Loos and Yeo (2022)] |
| MC4R | Melanocortin 4 receptor | Appetite regulation, energy balance | ,,,, [Adan et al. (2006)] [Hinney et al. (2010)] [ElhamKia et al. (2022)] [Loos (2025)] [Hayashi et al. (2025)] |
| SEC16B | SEC16 homolog B, endoplasmic reticulum export factor | Lipid metabolism, vesicle trafficking | , [Jo et al. (2024)] [Yonekawa et al. (2011)] |
| LINC02702 | Long intergenic non-protein coding RNA 2702 | Regulation of adipogenesis, gene expression | , [Gluba-Sagr et al. (2024)] [Jo et al. (2024)] |
| GNPDA2 | Glucosamine-6-phosphate deaminase 2 | Carbohydrate metabolism, energy balance | , [Jo et al. (2024)] [Wu et al. (2019)] |
| BDNF | Brain-derived neurotrophic factor | CNS appetite and body weight regulation | ,,; [Cordeira and Rios (2011)] [Urabe et al. (2013)] [Jo et al., 2024] [Loos (2025)] |
| ADCY3 | Adenylate cyclase 3 | cAMP signaling, energy balance | ,, [Pitman et al. (2014)] [Jo et al. (2024)] [Khani et al. (2024)] |
| RALGAPA1 | Ral GTPase activating protein catalytic alpha subunit 1 | BMI regulation | [Wong et al. (2022)] |
| IRX3/IRX5 | Iroquois homeobox 3/5 | Adipocyte differentiation via FTO locus | , [Bjune et al. (2025)] [Wong et al. (2022)] |
| ZNF259 | Zinc finger protein 259 | Metabolic syndrome, possible CVD link | , [Ellakwa et al. (2024)] [Jo et al. (2024)] |
Polygenic risk score
Polygenic risk scores (PRS) aggregate weighted effects from >1,100 common SNPs identified by GWAS (e.g., GIANT consortium), using methods like PRS-CS/LDpred or clumping + thresholding to account for linkage disequilibrium and effect size uncertainty, yielding a normally distributed score where top deciles confer obesity risk comparable to monogenic mutations. Clinically, PRS predict BMI trajectories from birth, stratify severe obesity risk, and identify lifestyle-responsive high-risk individuals, with healthy behaviors mitigating ∼30–50% of the genetic burden; however, limitations include modest variance explained versus total heritability (40%–70%), European-biased training data causing 50%–70% performance drops in non-Europeans, static scores missing dynamic gene-environment interactions, and weaker midlife prediction than serial BMI monitoring (Choe et al., 2022; Khera et al., 2019).
Metabolic health
Obesity phenotypes vary widely in metabolic health despite similar BMIs; notably, 10%–30% of individuals are classified as having metabolically healthy obesity (MHO). MHO is characterized by two or fewer metabolic syndrome components—such as normal glucose and lipid levels and an absence of hypertension—in contrast to metabolically unhealthy obesity (MUO), which presents with insulin resistance, dyslipidemia, and increased cardiovascular risk. The MHO associates with polygenic profiles that favor the distribution of subcutaneous fat (LINC02702 variants), preserving insulin sensitivity, and lower ectopic fat, while the MUO is connected to visceral adiposity and genetic burdens that amplify inflammation/lipotoxicity. Monogenic forms, for example, MC4R or LEP, typically manifest as MUO due to hyperphagia/energy imbalance disrupting the homeostasis on a metabolic level, though rare MHO-like presentations occur with partial penetrance. PRS stratify MHO/MUO transition risk, showing that high genetic burden accelerates the healthy-to-unhealthy conversion over time (∼30%–50% MHO lose status/decade) (Blüher, 2020).
gene FTO
Mutations and the most common genetic variants in the FTO gene (associated with fat mass and obesity) are associated with an increased risk of obesity through different mechanisms that influence energy balance and fat tissue function. The gene FTO is responsible for encoding the RNA demethylase enzyme, in which influences mRNA processing and regulates genes involved in adipogenesis, appetite control, and energy metabolism. Important single nucleotide polymorphisms (SNPs) in the FTO gene, such as rs9939609 and rs1421085, have been shown to be associated with a higher risk for high BMI, increased fatty mass, and altered dietary habits, including a tendency to consume energy-dense and high-fat foods. Mechanistically, these variants influence the expression of neighboring regulatory genes such as IRX3 and IRX5, which are responsible for the differentiation of adipocytes from energy-consuming beige cells to energy-storing white fatty cells, alongside reducing mitochondrial thermogenesis and promoting lipid accumulation. Functional studies also show that FTO gene variants have a great influence on appetite by modulating hypothalamic circuits and increasing ghrelin expression. Together, these molecular and behavioral effects contribute to a positive energy balance and increased susceptibility to obesity. The FTO gene offers potential targets for targeted therapeutic interventions (Kumar et al., 2022; Lan et al., 2020; Poosri et al., 2024; Yang et al., 2017).
gene MC4R
Mutations in the MC4R gene not only influence obesity risk through rare, highly effective variants that cause monogenic obesity (see above) but also interact with polygenic susceptibility to modulate obesity outcomes in broader populations. Recent large-scale studies show that carriers of obesity-associated MC4R mutations can exhibit highly diverse phenotypes depending on their polygenic risk score (PRS) for obesity. Individuals with high polygenic risk who also carry MC4R mutations have a significantly higher BMI and a higher risk of obesity than mutation carriers with low polygenic risk who remain normal weight or show only slight weight gain. This suggests that the polygenic background can either increase or attenuate the effect of MC4R gene mutations. Thus, polygenic susceptibility interacts with MC4R gene mutation status and influences the severity and penetrance of obesity. This underscores the complex genetic architecture of this common disease and the importance of integrating information about rare and common variants for personalized risk assessment and treatment strategies (Adamska-Patruno et al., 2021; Chami et al., 2020; Mohn et al., 2025; Wang et al., 2022).
gene SEC16B
Genetic variants near the SEC16B gene have been shown to be linked to polygenic obesity and an increased BMI in several populations, including Japanese and Caucasians. The SEC16B genes play a pivotal role in encoding a key protein involved in vesicle transport between the endoplasmic reticulum and the Golgi apparatus, which may have an influence on adipocyte function and energy regulation, although its specific metabolic role has not yet been fully elucidated. The common SNPs such as rs10913469 in SEC16B gene show a significant association with obesity risk, likely through the modulation of protein transport on an intracellular level and secretion pathways that influence fat storage and metabolism. These genetic effects add to other obesity-associated loci and thus contribute to the polygenic architecture of obesity. Further functional studies are needed to elucidate the precise biological mechanisms by which SEC16B variants influence obesity and metabolic homeostasis (Hotta et al., 2009; Sahibdeen et al., 2018; Shi et al., 2023).
gene LINC02702
Variants in the gene LINC02702 have been associated with polygenic obesity, where they influence obesity phenotypes, particularly through their potential regulatory functions during adipogenesis and lipid metabolism. Using a GWAS, the SNP rs486394 within LINC02702 was identified as significantly associated with increased BMI and metabolic traits related to obesity. Interestingly, the genetic results of this SNP differ between metabolically healthy obesity phenotypes and metabolically unhealthy obesity phenotypes, suggesting that LINC02702 influences not only obese individuals but also the metabolic health status of obese individuals. Long intergenic non-protein-coding RNAs (lncRNAs) such as LINC02702 gene are increasingly being recognized for their role in the regulation of gene expression and provide insights into complex genetic interactions underlying polygenic obesity (Jo et al., 2024).
gene GNPDA2
Variants in the GNPDA2 gene have been consistently associated with polygenic obesity and an increased BMI in various population studies through GWAS. The GNPDA2 gene encodes glucosamine-6-phosphate deaminase 2, which is involved in the hexosamine biosynthesis pathway that may influence adipogenesis and glucose metabolism. Studies of gene function suggest that altered GNPDA2 expression influences lipid accumulation and adipocyte differentiation, thereby contributing to increased fat mass. In addition, GNPDA2 is expressed in important metabolic tissues such as the hypothalamus, where it may play a role in nutrient sensing and energy balance regulation. The obesity-associated SNP rs10938397 near GNPDA2 shows a strong correlation with measures of central obesity such as waist circumference and waist-to-height ratio, underscoring its role in obesity distribution. These findings underscore the importance of GNPDA2 gene as a crucial gene contributing to the polygenic risk for fat mass through modulation of both metabolic and central nervous system signaling pathways (Gutierrez-Aguilar et al., 2021; Wu et al., 2019).
gene BDNF
Mutations and polymorphisms in the BDNF gene are associated with polygenic obesity due to their influence on energy balance, appetite regulation, and neurodevelopment. The common polymorphism Val66Met (SNP rs6265) in the BDNF gene alters the intracellular transport and secretion of the protein after maturation, thereby influencing hypothalamic signaling pathways that are critical for satiety and food intake control. Several studies from different research groups have confirmed an association between the Met allele and an increased BMI, an increased risk of obesity, and altered metabolic profiles, although the effects differ depending on the population studies and gender. In other words, the regulatory variants are very highly conserved regions of the BDNF gene and modulate its expression in the hypothalamus, thus influencing appetite control and energy homeostasis. The functional impact of these BDNF variants can also be influenced by other factors such as environmental factors, diet, and physical activity, which further contribute to the complex genetic architecture of polygenic obesity (Honarmand et al., 2021; McEwan et al., 2024; Miksza et al., 2023).
gene3 ADCY3
Mutations in the ADCY3 gene have been associated with polygenic obesity due to their influence on neural pathways regulating appetite and energy homeostasis. ADCY3 encodes adenylate cyclase 3, an enzyme that is primarily expressed in the primary cilia of hypothalamic neurons, where it catalyzes the production of cyclic AMP (cAMP), an important secondary messenger for appetite regulation and metabolic control. Variants of the ADCY3 gene that impair its function, especially homozygous loss-of-function mutations, have the ability to disrupt cAMP signaling pathways, which lead to excessive eating, severe obesity beginning in early childhood, insulin resistance, and delays in neurological development. Animal models confirm that loss of ADCY3 function disrupts leptin-melanocortin signaling pathways, particularly through its colocalization and interaction with MC4R in hypothalamic neurons, which are essential for normal body weight regulation. Moreover, certain ADCY3 gene polymorphisms are associated with obesity risk in various human populations, confirming its relation to polygenic obesity susceptibility. These findings emphasize how important ADCY3 is as a crucial genetic factor influencing obesity via central nervous system pathways that control feeding behavior and energy balance (Mohammed et al., 2024; Toumba et al., 2021).
gene RALGAPA1
The gene mutations found in the RALGAPA1 gene have been associated with polygenic obesity due to their pivotal role in intracellular signaling pathways that regulate energy balance and obesity. RALGAPA1 is responsible for encoding a GTPase-activating protein involved in the regulation of the Ral signaling pathway, which influences different cellular processes such as vesicle transport and cytoskeletal dynamics. Although direct functional studies on the role of RALGAPA1 in obesity are limited, the GWAS have found variants near or within the gene that correlate with increased BMI and obesity risk. These variants likely contribute with small additive effects within the polygenic architecture of obesity and influence fat accumulation and metabolic regulation. Research findings suggest that RALGAPA1 may interact with other obesity-associated genes to modulate hypothalamic control of appetite and peripheral metabolism, thereby contributing to the complex genetic predisposition observed in general obesity (Hinney and Hebebr, 2008).
/gene IRX3 IRX5
Mutations in the IRX3 and IRX5 genes have a significant influence on polygenic obesity, primarily through their regulatory effects on energy homeostasis, adipose tissue function, and hypothalamic appetite control. These genes are located near the FTO locus, the strongest genetic risk region for polygenic obesity, and the expression of IRX3 and IRX5 is modulated by obesity-associated variants within FTO through extensive enhancer-promoter interactions. The increasing expression of IRX3 and IRX5 genes in adipocytes lead to reduced thermogenesis of adipose tissue by promoting the storage of white fat over the formation of beige fat, thereby reducing energy expenditure. Moreover, in mouse models, the inhibition of Irx3 or Irx5 genes leads to lean phenotypes characterized by increased basal metabolic rate, increased adipose browning, decreased food intake, and a resistance to diet-induced obesity. The expression of these genes is also increased in hypothalamic neurons, suggesting their role in the central regulation of feeding behavior. These coordinated peripheral and central effects position IRX3 and IRX5 as important mediators of FTO-associated obesity risk and contribute to the complex polygenic architecture of obesity (Dou et al., 2021; Sobreira et al., 2021; Son et al., 2022).
gene mutation ZNF259
Variants in the ZNF259 gene are associated with polygenic obesity because they influence lipid metabolism and energy homeostasis. The gene ZNF259 is responsible for encoding a zinc finger protein that participates in regulating lipid profile and cell metabolism. Different genetic studies have identified polymorphisms within or near ZNF259 that are correlated with an increased BMI and dyslipidemia, both of which are risk factors for obesity. These variants contribute to obesity risk by modulating metabolic pathways that influence fat storage, insulin sensitivity, and systemic inflammation. Although the exact mechanisms are still being investigated, the cumulative effect of ZNF259 gene mutations in a polygenic context underscores its role as one of several genes with moderate effects on obesity susceptibility and metabolic dysregulation in affected individuals (Parra et al., 2017; Vázquez-Moreno et al., 2021).
Weight loss medications: scientific findings and clinical studies
The development of pharmacological agents for weight loss has intensified over the past decade, with several classes of anti-obesity medications targeting metabolic, hormonal, and appetite-regulating signaling pathways. Key breakthroughs include GLP-1 receptor agonists, dual incretin agonists, and newer, multi-hormonal therapies for obese patients that have been shown to demonstrate significant and sustained weight loss in both clinical trials and real-world practice.
Important classes of active substances and clinical study results
GLP-1 receptor agonists
Semaglutide: A GLP-1 receptor agonist administered once weekly results in significant and sustained weight loss in overweight and obese patients. In the randomized controlled trials STEP 5, SELECT, and STEP 1, participants who received 2.4 mg semaglutide subcutaneously lost 10%–15% or more of their body weight over a period of 68–104 weeks, which was significantly more than with placebo and behavioral interventions. At week 104, an estimated 77% of participants achieved a weight loss of ≥5% and over a third achieved a reduction of 20% or more. The most common side effects include mild to moderate gastrointestinal symptoms (clinicaltrials.gov/study/NCT03548935↗) (Garvey et al., 2022; Ghusn et al., 2022; Ryan et al., 2024).New oral agents: Oral semaglutide and other oral GLP-1 formulations (VK2735, amycretin) are currently being evaluated and show promising initial clinical results, which may improve accessibility.
Dual incretin receptor agonist
Tirzepatide: This once-weekly dual agonist of GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) is associated with even greater weight loss. In randomized studies, tirzepatide as an add-on to an intensive lifestyle program over 72 weeks resulted in an additional average weight loss of 18.4% (compared to a 2.5% increase with placebo). Meta-analyses confirm its superiority over placebo and GLP-1 therapy alone with consistent efficacy in patients with and without diabetes, although higher rates of gastrointestinal side effects are reported (ClinicalTrials.gov↗–NCT04660643↗) (Aryee et al., 2025; Lin et al., 2023; Wadden et al., 2023).
Triple and multi-hormonal agonist
Retatrutide: This novel active ingredient, which is administered once a week, acts on GLP-1, GIP, and glucagon receptors. A 48-week double-blind study found that 64%–100% of participants treated with retatrutide achieved ≥5% weight loss, and up to 26% of subjects lost 30% or more of their baseline weight. Using retatrutide is also shown to improve several cardiometabolic parameters and it demonstrates a favorable safety profile with comparable rates of adverse events to placebo (Jastreboff et al., 2023; Naeem et al., 2024).
Oral GLP-1 agonists
Orforglipron: A once-daily oral non-peptide GLP-1 receptor agonist has achieved significant weight loss in both Phase 1 and Phase 3 clinical trials. In the ACHIEVE-1 trial, adults with diabetes experienced an average weight reduction of about 16 pounds, corresponding to roughly 7.9% of their body weight, after 40 weeks of treatment with the highest dosage. In initial studies with healthy subjects, weight loss of ∼5.4 kg was observed after 4 weeks, with gastrointestinal events being the most common side effects (Ma et al., 2024; Pratt et al., 2023).
The addition of other active ingredients such as oral GLP-1 analogues and experimental combination therapies is currently being investigated and is expected to improve efficacy, ease of use, and accessibility in the coming years (Dolgin, 2025).
Comparative efficacy and real-world observations
In randomized controlled trials, semaglutide, tirzepatide, and retatrutide consistently result in double-digit percentage total weight loss, significantly outperforming previous obesity pharmacotherapy. Direct comparison studies and sequential studies demonstrate the superiority of dual and triple agonists (such as tirzepatide and retatrutide) over single-hormone therapies, suggesting a trend toward combination mechanisms for more effective weight loss (Lin et al., 2023; Naeem et al., 2024; Wadden et al., 2023).
Practical studies show a slightly lower average weight loss due to discontinuation of treatment and variable dosing, but significant benefits continue to be achieved when the therapy is adhered to (Tzoulis et al., 2024; Weiss et al., 2022). Safety profiles are generally favorable, with gastrointestinal side effects (nausea, vomiting, and diarrhea) being the most common. Serious adverse events are rare, and overall tolerability is high for the leading agents (Table 3) (Garvey et al., 2022; Jastreboff et al., 2023).
Modern anti-obesity medications—such as semaglutide, tirzepatide, retatrutide, and orforglipron—mark a paradigm shift in the pharmacological treatment of obesity. They enable significant weight loss in conjunction with improvements in metabolic risk factors, as demonstrated by numerous large-scale clinical trials. These anti-obesity medications pave the way for more accessible, convenient options (including once-daily tablets) and combination therapies, although their effectiveness in practice depends on long-term adherence and individual patient selection (Dolgin, 2025; Garvey et al., 2022; Jastreboff et al., 2023; Naeem et al., 2024; Ryan et al., 2024; Wadden et al., 2023).
| Drug | Mechanism | Formulation | Trial duration | Mean weight loss | % ≥5% body weight loss | Key trials |
|---|---|---|---|---|---|---|
| Semaglutide | GLP-1 RA | Weekly inject | 68–208 weeks | 10%–15% (;;) [Garvey et al., 2022] [Ghusn et al., 2022] [Ryan et al., 2024] | 67%–77% (;) [Garvey et al., 2022] [Ryan et al., 2024] | STEP, SELECT |
| Tirzepatide | GLP-1/GIP dual agonist | Weekly inject | 72 weeks | Up to 18.4% (;) [Lin et al., 2023] [Wadden et al., 2023] | 87% (;) [Lin et al., 2023] [Wadden et al., 2023] | SURMOUNT |
| Retatrutide | GLP-1/GIP/glucagon triple | Weekly inject | 48 weeks | Up to 24% (;) [Jastreboff et al., 2023] [Naeem et al., 2024] | 64%–100% (;) [Jastreboff et al., 2023] [Naeem et al., 2024] | Phase 2, 3 |
| Orforglipron | Oral GLP-1 RA | Daily pill | 4–40 weeks | 5%–8% (;) [Ma et al., 2024] [Pratt et al., 2023] | Not detailed | ACHIEVE-1 |
Links between weight loss anti-obesity medications and genetic mutations in obesity
Genetic mutations associated with obesity
As discussed, obesity has a strong genetic component, with both rare, highly effective mutations (monogenic forms) and several common genetic variants contributing to the risk. Key genes linked to severe or early-onset obesity include MC4R, LEP, LEPR, POMC, PCSK1, and FTO, all of which play pivotal roles in energy regulation and metabolic processes. The gene MC4R is the most commonly mutated gene in monogenic obesity, and variants of the FTO gene are closely associated with an increased body mass index and frequent obesity in the general population (Choquet and Meyre, 2011; González Jiménez, 2011; Herrera et al., 2011; Loos and Yeo, 2022; Mahmoud et al., 2022). In patients with extremely high BMI (e.g., >40 kg/m2), gene mutations that influence these signaling pathways are relatively common (Al-Humadi et al., 2023).
The impact of genetic mutations on the effectiveness of weight loss medications has been demonstrated, with variations in genes influencing the response and outcomes of treatment.
GLP-1 receptor agonists (semaglutide, liraglutide, tirzepatide, etc.)
The leading anti-obesity medications (GLP-1 receptor agonists, dual/triple incretin agonists, oral GLP-1 tablets) have been studied for their effectiveness in different genetic backgrounds:Recent multi-biobank studies from different research groups involving more than 10,000 individuals have found that common genetic variants associated with obesity, including those in MC4R, FTO, and polygenic obesity risk scores, had no clinically significant impact on the efficacy of GLP-1 receptor agonists for weight loss. These anti-obesity medications, such as semaglutide and tirzepatide, achieve similar levels of weight loss irrespective of genetic background, suggesting that patients with high-risk mutations for obesity benefit to a similar extent as patients without such variants (German et al., 2025; Wong et al., 2025).SNPs of the GLP1R gene: Other pharmacogenetically relevant loci have presented only minor and inconsistent associations with weight loss in smaller studies, suggesting that the known mutations of obesity genes cause only minor differences in drug response (BouSaba et al., 2023; Dawed et al., 2023; German et al., 2025).
Influence of genetic predisposition
Some research groups have suggested that a lower overall genetic predisposition to obesity may be correlated with slightly greater weight loss under GLP-1 therapy, but the variations observed are generally small and are not considered to limit the treatment benefit for individuals at high genetic risk (Levy et al., 2024). Genetic variability plays a more pivotal role in the development of obesity than in the effectiveness of pharmacological interventions for weight loss (Cifuentes et al., 2025; German et al., 2025; Wong et al., 2025) (Table 4).
| Main genes involved | Associated with obesity | Impact on drug response |
|---|---|---|
| MC4R, LEP, LEPR, FTO | Strong effect, monogenic/polygenic forms (;;;;;) [Loos and Yeo, 2022] [Mahmoud et al., 2022] [Choquet and Meyre, 2011] [Herrera et al., 2011] [González Jiménez, 2011] [Tirthani et al., 2025] | Little to no clinically significant difference in weight loss with GLP-1 anti-obesity medications;) [Wong et al., 2025] [Levy et al., 2024] |
| GLP1R, CNR1 | Minor influence on specific responses (;) [BouSaba et al., 2023] [Dawed et al., 2023] | No consistent or strong effect detected |
Clinical implications
The most effective and commonly used weight loss anti-obesity medications—GLP-1 receptor agonists (injectable and oral) and dual and triple incretin agonists—show broad efficacy regardless of individual genetic risk for obesity. Current findings support prescribing these anti-obesity medications to people with a high genetic predisposition to obesity, as their weight loss results are comparable to those of individuals without significant obesity-associated mutations. While personalized genetic testing can identify rare cases in which alternative treatments such as other anti-obesity medications or bariatric surgery may offer additional benefits, for the majority of patients, genetic mutations do not significantly influence the likelihood of successful weight loss through pharmacotherapy (Cifuentes et al., 2025; German et al., 2025; Wong et al., 2025).
Discussion
Obesity is a complex clinical challenge caused by environmental influences and genetic predisposition, which has been uncovered by intensive genetic research. Monogenic obesity results from rare, highly penetrant mutations that primarily affect neuroendocrine regulators such as MC4R, LEP, LEPR, POMC, and PCSK1 and syndromic genes, including Bardet-Biedl variants. These mutations show severe, early-onset phenotypes and define discrete clinical entities that are suitable for targeted interventions such as MC4R agonists. Conversely, polygenic obesity arises from the additive effect of numerous common variants—over 1,100 loci have been identified in GWAS—each of which has a moderate phenotypic influence. The important polygenic genes such as FTO, MC4R, SEC16B, and LINC02702 together modulate appetite, energy balance, and adipogenesis via overlapping neuroendocrine signaling pathways, illustrating a common biological framework with monogenic forms.
The intersection of monogenic and polygenic obesity signalling pathways highlights the critical role of neuroendocrine signalling networks, especially the leptin-melanocortin pathway, in the development of obesity. Importantly, gene-environment interactions shape the phenotypic spectrum, which complicates risk prediction but offers intervention loci. Polygenic risk scores are powerful predictive tools but need to be validated in independent populations.
Pharmacological advances, particularly GLP-1 receptor agonists and dual/triple incretin therapies, have shown efficacy in weight decrease irrespective of genetic background and offer promising precision treatments for obesity. Genetic background has minimal influence on response to therapy, suggesting broad applicability. However, personalized medical approaches that leverage genetic diagnostics could optimize patient selection and identify new therapeutic targets (Ko et al., 2025).
The integration of genetic examination into routine care remains a challenge due to cost, complexity, and incomplete understanding of all relevant loci. The growth of polygenic risk models and the unraveling of mechanistic signaling pathways will improve the precision of prevention and treatment. Ultimately, multidisciplinary approaches combining genomics, lifestyle changes, and new therapeutics will be crucial in combating the obesity epidemic.
Conclusion
This overview highlights the complex genetic architecture of obesity, ranging from rare monogenic mutations in important neuroendocrine genes to widespread common variants that contribute to polygenic risk. The integration of genetic insights has improved understanding of biological mechanisms and advanced the development of effective pharmacotherapies, marking a paradigm shift toward precision medicine for obesity. Although current anti-obesity medications are effective regardless of genetic background, genetic risk stratification using polygenic scores promises individualized prevention and tailored treatment strategies. Further research on gene-environment interactions, more comprehensive genetic screening, and functional characterization of obesity-associated loci are essential. Future efforts must focus on translating genomic discoveries into accessible clinical tools to improve obesity treatment, alleviate comorbidities, and improve treatment outcomes for patients worldwide.
This review elucidates obesity’s genetic architecture, contrasting rare monogenic forms (e.g., MC4R, LEP, and POMC gene mutations in leptin-melanocortin signalling pathways) with common polygenic forms (like FTO and SEC16B). Key findings highlight shared neuroendocrine mechanisms, gene-environment interactions, polygenic risk scores for stratification, and GLP-1/incretin agonists’ efficacy across genetic backgrounds.
These align with objectives by advancing precision pharmacotherapy: genetic insights enable risk prediction and tailored interventions despite challenges in screening and interactions. Future priorities include expanded genomics, functional studies, and clinical translation for optimized outcomes.