Obesity is a multifactorial and complex disease that often manifests in early childhood with a lifelong burden. Polygenic and monogenic obesity are driven by the interaction between genetic predisposition and environmental factors. Polygenic variants are frequent and confer small effect sizes. Rare monogenic obesity syndromes are caused by defined pathogenic variants in single genes with large effect sizes. Most of these genes are involved in the central nervous regulation of body weight; for example, genes of the leptin–melanocortin pathway. Clinically, patients with monogenic obesity present with impaired satiety, hyperphagia and pronounced food-seeking behaviour in early childhood, which leads to severe early-onset obesity. With the advent of novel pharmacological treatment options emerging for monogenic obesity syndromes that target the central melanocortin pathway, genetic testing is recommended for patients with rapid weight gain in infancy and additional clinical suggestive features. Likewise, patients with obesity associated with hypothalamic damage or other forms of syndromic obesity involving energy regulatory circuits could benefit from these novel pharmacological treatment options. Early identification of patients affected by syndromic obesity will lead to appropriate treatment, thereby preventing the development of obesity sequelae, avoiding failure of conservative treatment approaches and alleviating stigmatization of patients and their families.
Obesity is a complex, multifactorial disease that can be classified into common polygenic obesity and rare obesity syndromes, including monogenic obesity.
Most monogenic obesity traits result from pathogenic variants in single genes converging in the leptin–melanocortin pathway.
Targeting central pathways of energy expenditure with, for example, MC4R agonists provides new and promising treatment options for patients with monogenic obesity.
Polygenic obesity results from an interplay among numerous genetic and environmental factors.
Polygenic risk scores and massively parallel sequencing approaches will help the early identification of obesity predisposition.
New precision medicine approaches based on genetic obesity traits might help tackle the obesity pandemic.
According to the World Health Organization (WHO), approximately 39 million children under the age of 5 years had overweight or obesity in 2020 (ref.1). The prevalence of severe obesity is particularly alarming. Depending on the study and criteria (Table 1) applied, the reported prevalence of severe childhood obesity ranges from 1.96% to 6.30% within the general population2. Interestingly, a 2018 study discovered that adolescents with obesity experienced the most rapid weight gain at an age of 2–6 years3. In parallel to an increase in BMI in early childhood, adipose tissue mass expands and the first signs of adipose tissue dysfunction appear, such as adipocyte hypertrophy, inflammation and macrophage infiltration, and dysregulation of adipokine secretion4. The early onset of obesity is clearly linked to the development of cardiovascular and metabolic comorbidities, with preclinical manifestations occurring in adolescence, and ultimately leading to an increase in mortality in adulthood5. Obesity is a frequent, serious, complex and chronic, relapsing disease, recognized as such by the leading professional societies6,7. Based on the genetic contribution, obesity can be classified into two main groups: syndromic obesity (which includes obesity syndromes associated with neurodevelopmental disorders as well as monogenic obesity syndromes) and common polygenic obesity. Common childhood obesity arises from the interaction of individual genetic predisposition and our obesogenic environment.
Since early 2020, the COVID-19 pandemic has intersected with the obesity pandemic, and showed the particular vulnerability of children with existing obesity to further excessive weight gain and the clinical burden associated with lockdowns8,9,10. Therefore, preventing and treating obesity as early as possible is of the utmost clinical importance and social relevance.
Individuals living with obesity are often accused of failure to adopt a healthy lifestyle, even by health-care professionals. This assumption leads to stigmatization and is associated with psychological harm11. Knowledge about the pathological mechanisms of obesity, including genetics, helps reduce weight stigma12. Reduction of stigmatization through the gain of knowledge and education is an important aim of genetic studies in the context of body weight regulation and obesity.
In this Review, we consider the heritability of body weight and genetic classifications of obesity, including common polygenic obesity and rare monogenic obesity. We discuss clinical features of early-onset monogenic obesity, as well as the hallmarks of monogenic obesity caused by pathogenic variants in different single genes. Finally, we highlight novel pharmacological treatment options for monogenic obesity targeting the central melanocortin pathway, as well as other innovative potential therapeutic avenues.
Heritability of body weight
Body weight variance, similar to other anthropometric measures, is highly heritable (Box 1). Seminal twin and adoption studies at the end of the 1980s and 1990s13 underscored that genetic factors have a remarkable role in body weight regulation14. Twin studies have found the highest and most consistent heritability estimates ranging from 0.6 to 0.9 for explained BMI variance15. Except for the postnatal period, for which a heritability of 0.4 had been found, heritability estimates of BMI are not substantially affected by age16. Heritability estimates of body weight and obesity derived from family and adoption studies are mostly considerably lower than in twin studies (0.25–0.7)15. Of note, both direct and indirect genetic effects compose the genetic component of obesity. For example, if in a monozygotic twin pair both infants are frequently hungry (a direct genetic effect), the carer will probably feed them often, even if the twins were separated at birth (an indirect genetic effect)17. The genetic underpinnings of obesity are complex and apply to metabolic as well as behavioural factors; more than half of the variance in body weight is genetically determined18.
In large epidemiological studies, parental obesity is by far the strongest risk factor for obesity in childhood and adolescence19, particularly if both parents are affected20. Stronger maternal than paternal effects have been found in several studies21. Twin and other family studies have implied that the strong predictive value of parental BMI mainly arises from genetic rather than shared environmental factors15. Socio-economic status is another important risk factor for paediatric obesity: in children with a low socio-economic status the odds ratio for obesity is more than twofold higher than in children with a high socio-economic status19.
Although genome-wide association studies (GWAS) have provided valuable insights, the identified genetic variation only explains a small fraction of the heritability of body weight. Identified variants mostly have small effect sizes. A consensus explanation for this ‘missing heritability’ in complex diseases has not yet emerged22. Possible explanations include analytical limitations, small effect sizes, rare variants, variants not picked up owing to methodological limitations (for example, chromosomal rearrangements), imprecise heritability estimates, developmental aspects, non-additive or epistatic mechanisms, parental contributions, epigenetic effects, interactions between variants, expression of non-coding RNAs or transgenerational genetic effects23.
Genetic classification of obesity
Based on the genetic contribution, obesity was historically classified into three main groups, common polygenic obesity, syndromic obesity and monogenic obesity. This traditional view has been revisited, as certain forms of monogenic obesity can be accompanied by neurodevelopmental and/or psychiatric disorders; therefore they can also be regarded as syndromes. Thus, we suggest that the group of obesity syndromes should be distinguished from common, polygenic forms of obesity24,25. Even this categorization might be an oversimplification, as the influence of genetics on obesity can be seen as a continuous spectrum25.
Polygenic forms of obesity
The most common form of obesity is multifactorial and driven by the interaction between polygenic predisposition and environmental factors. The polygenic factors commonly act additively, so that the effects of all single alleles sum up to a combined effect size (Box 2). A 2019 study identified and validated a polygenic predictor containing 2.1 million common variants to quantify obesity susceptibility26. The predictor was tested in more than 300,000 individuals from birth to middle age. In the group of middle-aged adults, a 13-kg weight difference (gradient) was observed between those with a high risk score and those with a low risk score. Additionally, a 25-fold gradient in risk of severe obesity was observed across polygenic score deciles26. Hence, polygenic risk scores (PRS) might help to estimate individual risk of progressive severe obesity. However, such risk scores would be even more precise if additional non-genetic clinical and environmental factors could be incorporated. Within a longitudinal birth cohort, the differences in birthweight across score deciles were minimal26. However, in early childhood the gradient became substantial and even reached 12 kg by 18 years of age. Thus the effect size of a polygenic score can be similar to that of rare, pathogenic variants that cause monogenic obesity. Despite the impressive sample size and number of variants included26, the finding of only 23.4% of BMI variability explained indicates that unknown or unidentified factors exist that might in the future explain this missing heritability.
Syndromic obesity with signs of neurodevelopmental disorder
The form of obesity that was historically referred to as syndromic usually starts early in life and is associated with other clinical characteristics such as dysmorphic features, short stature, organ-specific developmental abnormalities and malformations, as well as neurodevelopmental deficits such as delayed learning and walking, intellectual impairment and autism spectrum disorders27,28. Prominent examples are Prader–Willi syndrome and Bardet–Biedl syndrome. More than 80 distinct syndromes have been described to date to be associated with childhood obesity and their genetic causes and phenotypes are described elsewhere27,28.
Monogenic forms of obesity
Monogenic obesity is caused by genetic variations in single genes (Table 2). Of note, affected genes are usually involved in the central nervous system regulation of hunger and satiety and are mostly linked to the hypothalamic leptin–melanocortin pathway29 (Fig. 1). The genetic risk variants that cause monogenic obesity are infrequent. However, in children who were referred to a tertiary centre due to suspicion of an underlying medical cause of obesity, the reported prevalence values can reach 13%30. Frequencies higher than 13% have been reported in consanguineous populations24,31,32. This rate might be expected to increase in the future with the emergence of massive parallel sequencing technology24. In fact, an analysis of the Avon Longitudinal Study of Parents and Children cohort of English children found a frequency of 0.30% for pathogenic melanocortin 4 receptor gene (MC4R) variants33. However, even with the use of specific obesity gene panels and modern exome sequencing technology, the identification of patients with known forms of monogenic obesity will only infrequently occur. In addition to classic genetic mechanisms, accumulating evidence indicates that epigenetic mechanisms have a role in the development of obesity34,35.
Clinical features of early-onset obesity
Definitions and cut-offs
To diagnose early-onset obesity and to perform comparable clinical studies, clear and uniform definitions are urgently needed. The definitions provided in the current clinical practice guidelines on paediatric obesity from the Endocrine Society24 are based on the Centers for Disease Control and Prevention (CDC) growth charts in children aged 2–19 years and on WHO child growth standards in infants aged <2 years (Table 1). Of note, national guidelines might differ from international definitions and recommendations. The CDC provides a BMI and BMI-for-age percentile calculator for children and teens on their website.
Risk factors for paediatric obesity
Three major risk factors for childhood obesity exist; these are genetic predisposition, parental overweight and lower socio-economic status. Beyond these factors, large epidemiological studies have identified that perinatal factors (such as high maternal weight gain during pregnancy, high birthweight and formula feeding) impose an increased obesity risk, with even stronger associations than ‘classic’ lifestyle factors (such as sleep duration, media consumption or physical activity)19. Thus, perinatal factors should be regarded in the clinical evaluation of children with obesity. Of particular note, high birthweight was shown to be associated with obesity later in life36 and children large for gestational age were more likely to have a high BMI in childhood and adolescence than children born with a normal weight3. This association needs to be differentiated from the increased risk for type 2 diabetes mellitus (T2DM) and cardiovascular disease in children who were born small for gestational age according to the Barker hypothesis. In particular, rapid catch-up growth in infancy drives the progressive transition to central obesity and insulin resistance in those children born small for gestational age37.
A 2018 population-based study analysed the BMI dynamics in 51,505 children3. The annual change in BMI standard deviation score (BMI-SDS) during childhood was assessed in relation to the occurrence of underweight, normal weight, or overweight and obesity in adolescence. The respective groups were assigned based on national (German) reference data3. As expected, normal weight or underweight children had a stable BMI-SDS of around zero, across the range of measurements. In contrast, children with overweight or obesity had increased BMI-SDS scores from infancy onwards, beginning at 1 year of age. As already mentioned, the annual increase in BMI-SDS was highest between the ages 2 years and 6 years. Similar to BMI, growth dynamics in children with obesity are substantially different from that in children with normal weight. Children with obesity are significantly taller in early childhood, with height SDS ranging from 0.4 to 1 standard deviations above the reference38,39,40,41. In children with obesity, earlier puberty, a blunted pubertal growth spurt, alterations in sex hormone profiles and advanced bone age might explain subsequent normalization in final height compared with children with normal weight39,40.
Features of monogenic obesity syndromes
The BMI trajectories of children with certain forms of monogenic obesity are clearly different from those with polygenic obesity42. Most monogenic forms are characterized by a rapid onset of weight gain after birth, with the most rapid increase in BMI in the first year of life. For example, patients with congenital leptin or leptin receptor deficiency had a BMI of >27 kg/m2 at the age of 2 years and their BMI was >140% of the 95th percentile. At the age of 5 years their BMI was >33 kg/m2 and >184% of the 95th percentile in both patient groups42. Patients with congenital leptin or leptin receptor deficiency do not have normal pubertal development due to hypogonadotropic hypogonadism43,44,45. Reports on linear growth are inconsistent. In one study, patients with leptin deficiency were taller than the mid-parental median46. By contrast, in other studies, patients with leptin or leptin receptor deficiency had normal growth in childhood but reduced final height due to the absence of a pubertal growth spurt44,47. Patients heterozygous for pathogenic variants in MC4R show less pronounced weight gain in the first 2 years of life, but severe obesity later in childhood42 and frequently have tall stature30.
In monogenic obesity, central hypothalamic and neuroendocrine pathways can be impaired24,48, which is consistent with reports from patients and/or their families of hyperphagia with food-seeking or even food-stealing behaviour and insatiable hunger. Hyperphagia can be described as increased energy intake compared with control individuals or as eating an amount higher than predicted for body size or composition49. This trait often accompanies a preoccupation for food, presenting, for example, as food-seeking behaviour49. Satiety describes the control of appetite and refers to periods between meals, whereas satiation is the control of meal size50. These processes can be measured by questionnaires50.
Some features of monogenic obesity are more specific to certain gene alterations (see below), such as impaired pubertal development, increased predisposition to infections or diarrhoea and hypopigmentation. Of note, cognitive development is usually normal in patients with monogenic obesity. Motor development might seem to be delayed, but this effect is at least to some extent attributable to excess body mass. Based on these observations, genetic testing should be considered if ‘red flags’ indicative for monogenic obesity are present (Box 3). Current clinical practice guidelines recommend genetic testing in patients with severe early-onset obesity (before 5 years of age) and clinical features of genetic obesity (in particular severe hyperphagia) and/or a family history of severe obesity24.
If genetic testing is proposed, the low likelihood of finding an underlying genetic cause should be openly communicated to patients with obesity and their families, to prevent falsely high expectations. Furthermore, if a genetic variant is reported, particularly a de novo variant, the functional impairment must be shown experimentally to be the cause of the phenotype. The clinical cause is furthermore dependent on the presence and degree of impairment of function, which has been shown for MC4R pathogenic variants51,52 but also for LEPR and PCSK1 variants48,53,54,55,56.
Hallmarks of monogenic obesity traits
The most common forms of monogenic obesity and those with indication for available pharmacological treatments are outlined here, in the order from peripheral signals that converge centrally to MC4R (Fig. 1 and Table 2).
Congenital leptin deficiency
Leptin is a 16-kDa protein and adipokine57,58. It exerts its functions via binding to and activating the long form of the leptin receptor, which results in the activation of various signalling cascades, such as phosphorylation of STAT3 (ref.59). The serum levels of leptin correlate positively with body adipose mass and BMI, with strong variability in the levels occurring at extremes of BMI60. Via central and peripheral routes, leptin affects a wide range of physiological processes including energy balance, metabolism, endocrine regulation and immune function57,58. Leptin represents a peripheral signal for energy sufficiency to the central nervous system. A low level of the hormone corresponds to a low energy state of the adipose tissue lipid stores. Critically low levels of leptin induce a range of responses to preserve or restore the energy reservoir, among them altered behavioural, metabolic, endocrine and immune responses61.
Pathological variants in LEP lead to congenital leptin deficiency or dysfunction43,62,63,64,65. Patients present with hyperphagia, increased food seeking and impaired satiety. Born with normal weight, patients rapidly gain weight after birth and develop severe obesity associated with hyperinsulinaemia, dyslipidaemia and hepatic steatosis62. Another cardinal sign of leptin deficiency or dysfunction is hypogonadotropic hypogonadism and delayed pubertal development, whereas recurrent severe infections are reported in some but not all patients62,63,64,66,67,68. In mice, hyperleptinaemia promotes obesity-associated hypertension69. Thus, one might expect that a disturbance in the leptin–leptin receptor system leads to hypotension. However, four out of six studied patients with leptin deficiency had high blood pressure70, which suggests leptin-independent pathomechanisms in the development of hypertension. In rats, leptin was found to regulate the hypothalamic–pituitary–thyroidal axis71,72. However, thyroid dysfunction is not a constant feature of leptin deficiency or dysfunction63,67,73.
In 1997, congenital leptin deficiency was first described as an autosomal recessive form of severe early-onset obesity in two children of a consanguineous family originating from Pakistan63. Of note, circulating levels of leptin were almost non-detectable in both patients. Since this initial description, a total of 18 distinct variants have been reported in over 60 patients worldwide62. Several variants cause defects in leptin protein production and/or secretion, which leads to classic leptin deficiency43,62,63. This disease can be diagnosed by confirming the absence of immunoreactive leptin in the circulation. However, a LEP variant (c.298G>T, p.D100Y) was described that is produced and secreted but is biologically inactive. The genetic alteration lies within a region of the protein that is responsible for docking on to the receptor, thereby rendering the variant incapable of binding to the leptin receptor and causing congenital leptin dysfunction64. In patients with common polygenic obesity, total immunoreactive and bioactive blood levels of leptin are concordant74,75. By contrast, immunoreactive blood levels of leptin in the patients with congenital leptin dysfunction are high, whereas bioactive blood levels of leptin are below the detection limit74. Therefore, the correct diagnosis of congenital leptin dysfunction could be missed if just a classic leptin radioimmunoassay or enzyme-linked absorbance assay is performed for diagnostic purposes64. Of note, a DNA sequencing approach can detect such pathogenic variants. Therefore, genetic testing is highly recommended in patients with suspected monogenic obesity, for example, through an obesity gene panel or exome-based sequencing.
Congenital leptin receptor deficiency
Congenital leptin receptor deficiency is a rare disease with autosomal recessive inheritance and a phenotype that is highly comparable to that in leptin deficiency or dysfunction44,76,77. It was first described in a consanguineous family from northern Algeria76. In a 2019 paper, 45 distinct LEPR variants were reported in the literature in a total of 88 patients77. The genetic alterations include single amino acid changes, insertions, duplications and deletions, as well as nonsense risk variants predicted to cause truncation of the leptin receptor protein77,78. The functional impairment caused by these risk variants needs to be proven to assess the causality of the genetic variation, and this knowledge might guide future treatment decisions79. The predicted prevalence of LEPR deficiency is 1.34 per 1 million people. Based on these numbers, one would expect that there are 998 patients with LEPR deficiency in Europe. The fact that the number of published cases is substantially lower suggests considerable underdiagnosis of this disease77.
Patients with variants in the LEPR gene are normal weight at birth, but then rapidly exhibit pronounced food-seeking behaviour, hyperphagia and impaired satiety28,44,76. This phenotype leads to rapid weight gain and severe obesity associated with hyperinsulinaemia, dyslipidaemia and hepatic steatosis28,44,76. Hypogonadotropic hypogonadism is a constant feature of leptin receptor deficiency28,44,76,77, whereas recurrent severe infections are less frequently observed77. Pituitary hormone deficiencies are found in one-third of patients77.
The SH2B adapter protein 1 (SH2B1) is a crucial molecule in leptin-mediated signal transduction that enhances the downstream signal by JNK2-dependent and JNK2-independent mechanisms80. In 2010, deletions on chromosome 16p11.2, an area where SH2B1 is located, were found to co-segregate with obesity, and heterozygous carriers of deletions display severe hyperphagia and severe insulin resistance81. Shortly thereafter, loss of function variants in SH2B1 were identified as a monogenic cause of hyperphagia and early-onset obesity along with maladaptive behaviour82,83. SH2B1 also serves as an adaptor molecule in the insulin signalling cascade and might act as a central as well as a peripheral regulator of glucose homeostasis and insulin sensitivity independently of body weight84. Thus, it is not surprising that affected patients have severe insulin resistance that is disproportionate to the degree of obesity81. Considering its action as a promoter of leptin signalling in the MC4R pathway, treatment with MC4R agonists might be effective as a therapy in these patients. In the first phase II trials, half of the patients with SH2B1 deficiency or 16p11.2 deletion responded with clinically relevant weight loss. Such a clear separation of responders and non-responders might be due to heterogeneity in the underlying genetic causes85.
The proopiomelanocortin (POMC) gene encodes a pituitary preproprotein that is processed into several bioactive neuroendocrine peptides via the proprotein convertase subtilisin/kexin type 1 (PCSK1)29. Among them is α-melanocyte-stimulating hormone (α-MSH), which acts via the MC4R to suppress appetite and food intake29. Homozygous or compound heterozygous variants lead to POMC deficiency, also known as ‘early-onset obesity, adrenal insufficiency and red hair’. This autosomal recessive disorder was first described in 1998 (ref.86) and is characterized by severe hyperphagia that leads to severe early-onset obesity, secondary hypocortisolism and pigmentary abnormalities such as pale skin and red hair, with the pigment phenotype being dependent on the genetic background of the individual. Hypoglycaemia, hyperbilirubinaemia and life-threatening cholestasis might be observed in the first months of life86. In total, 14 distinct variants have been described in 17 patients87. In addition to these classic genetic alterations, variation in the DNA methylation status of POMC was shown to be associated with obesity88. DNA methylation is influenced by maternal nutrition during pregnancy89, which underscores the modulating and direct role of environmental factors on molecular pathways that regulate energy balance and hence body weight.
Variants in PCSK1 in the homozygous or compound heterozygous state lead to a complex clinical phenotype, with early-onset obesity but also enteropathy with severe diarrhoea and neuroendocrine problems, among them glucocorticoid deficiency, hypogonadism and abnormal glucose homeostasis90,91,92,93. These features result from the failure of PCSK1 to process active hormones from prohormones; for example, α-MSH from POMC in the hypothalamus or glucagon-like peptide 1 (GLP1) or GLP2 from proglucagon in the small intestine54,90,91,92,93. To date, 26 patients have been reported in the literature94. Interestingly, variants in PCSK1 have also been identified in GWAS to be associated with childhood obesity95. Hence, the influence of PCSK1 variants on obesity ranges from clear monogenic presentation to complex polygenic associations. Therefore, the functionality of an individual’s gene variant needs to be assessed56 before treatment with MC4R agonists can be initiated.
First described in 1998 as a relevant factor for severe obesity in humans96,97, MC4R deficiency so far is the most frequent form of monogenic obesity52,98. Variants in MC4R are estimated to be found in 2–5% of paediatric and adult patients with obesity29,52,99. Some of these patients might respond well to treatment with MC4R agonists such as setmelanotide100. More than 150 variants have been described, and homozygous, compound heterozygous and heterozygous variants have a role in the development of obesity29,52,99. Most variants reduce the function of the MC4R, which leads to hyperphagia, severe obesity and severe hyperinsulinaemia, which sometimes occurs along with increased lean mass and increased linear growth101.
Effects on body mass for loss of function MC4R risk variants are in the range of 15–30 kg increased weight101. Also, in 2004, a gain of function MC4R variant (V103I) was described that decreases body weight by ~1.5 kg102. Data published in 2019 confirmed the relevance of both loss of function and gain of function variants in weight regulation103. MC4R is a G protein-coupled receptor (GPCR) and the functionality of variants was typically proven based on the capacity to induce Gs signalling. However, insights published in 2020 led to a more detailed view of MC4R signalling, which uncovered that some variants (for example, V103I and H158R) are biased towards the Gq/11 pathway by endogenous agonists104. This finding once more underscores the necessity for a detailed and comprehensive functional characterization of genetic variants.
Carriers of gain of function variants in MC4R present with lower BMI as well as lower odds of cardiometabolic sequelae such as T2DM and coronary artery disease than non-carriers of these variants102,103. These gain of function variants exhibit a signalling bias, with an increased recruitment of β-arrestin to the MC4R along with increased cAMP levels in heterologous cell systems and increased and sustained phosphorylation of ERK1/2 (ref.103).
Biased signalling is an interesting phenomenon known for GPCRs105. Of note, the exomes of 645,626 individuals were sequenced and 16 genes with an exome-wide association with BMI were identified. Among them were five brain-expressed GPCRs106. This finding suggests that other GPCRs might act as fine tuners of body weight, also in the heterozygous state.
The Gαs protein is encoded by GNAS and mediates GPCR signalling. The classic obesity syndrome Albright hereditary osteodystrophy is caused by pathogenic variants in GNAS. Patients present with developmental delay, short stature and skeletal abnormalities. Owing to maternal imprinting, pathogenic variants on the maternal allele also cause obesity and hormone resistance to parathyroid hormone (pseudohypoparathyroidism). A sequencing approach published in 2021 in 2,548 children with severe obesity revealed 22 were heterozygous carriers of GNAS pathogenic variants107. Nearly all pathogenic variants in GNAS lead to impaired MC4R signalling. The authors suggested that screening of children with severe obesity for GNAS deficiency might enable early diagnosis and improved clinical outcomes107. Affected patients might benefit from treatment with melanocortin agonists. Variant frequencies in normal weight control individuals were not described.
Carboxypeptidase E (CPE) is an enzyme that catalyses the removal of carboxy-terminal arginine or lysine residues from polypeptides, after being processed by proprotein convertases108. This enzyme is involved in the biosynthesis of peptide hormones and neuropeptides. A truncating pathogenic variant in CPE resulted in undetectable mRNA expression in blood cells derived from a patient with severe obesity. In addition to severe obesity, the patient had hypogonadotropic hypogonadism, abnormal glucose homeostasis and intellectual disability109. In 2021, novel homozygous CPE loss of function variants were described in four individuals from three unrelated consanguineous families110. All affected individuals had severe obesity and showed endocrine anomalies (hypogonadotropic hypogonadism and central hypothyroidism) as well as neurodevelopmental delay. The authors of this study named this specific, recognizable clinical phenotype Blakemore–Durmaz–Vasileiou syndrome110.
Nuclear receptor coactivator-1 (NCOA1; also known as steroid receptor coactivator 1, SRC1) modulates the function of nuclear hormone receptors and transcription factors in enhancing or suppressing the expression of target genes111. Based on the fact that mice with a deletion of Ncoa1 in POMC neurons display increased food intake and obesity, exome sequencing and corresponding resequencing data from a cohort of patients with severe early-onset obesity and respective control individuals were analysed112. In the obesity group, the authors identified 15 heterozygous variants in NCOA1, which caused an impairment of leptin-induced POMC expression, whereas four other variants in NCOA1 found in the control group had no effect. A detailed phenotypic description of patients with these variants is not available at this point.
Treatments for monogenic obesity
Data on lifestyle interventions in patients with monogenic obesity are scarce. One study analysed the effect of a 1-year lifestyle intervention based on exercise, behaviour counselling and nutritional counselling in paediatric patients with MC4R variants113. Children with pathogenic variants lost weight to an amount comparable to that in age-matched and BMI-matched control children without such alterations113,114; however, they had greater difficulties in maintaining the weight loss113. By contrast, a study in Danish children found that an intervention programme at a tertiary centre for 1 year failed to reduce BMI-SDS in children with MC4R-related obesity115. Studies on surgical interventions in monogenic obesity are also scarce116,117,118. Currently, no clear statements have been made on safety and efficacy116; therefore we conclude that surgery is not a primary treatment option116.
Single case reports describe the diagnostic odyssey of patients with congenital leptin receptor deficiency and the failure of several therapeutic approaches. These include weight loss programmes, outpatient and inpatient psychotherapy and bariatric surgery, that mostly have unsatisfactory results119,120. These examples demonstrate that early genetic diagnostics are required in severe early-onset obesity to avoid the frustrating failure of therapy or even potentially harmful surgical intervention120.
Pharmacological treatment options
Pharmacological treatment options for common polygenic obesity with long-term effects are very limited121. A number of medications for weight loss in adults have received FDA approval121. Three of them were approved for use in adolescent obesity: the lipase inhibitor orlistat, the norepinephrine reuptake inhibitor phentermine, and the GLP1 receptor (GLP1R) agonist liraglutide. In Europe, liraglutide is the only pharmacological treatment option24,122,123,124,125 approved by the EMA, but is largely not reimbursed by health insurance providers (for example, in Germany).
In the past 10 years, genetic analyses have led to individualized treatment options for some types of monogenic obesity.
Comparable to other endocrine disorders characterized by the absence of certain hormones, congenital leptin deficiency or leptin dysfunction can be treated by hormone supplementation therapy. In patients with leptin deficiency, subcutaneous administration of human recombinant leptin at a dose of 0.03 mg/kg of lean body mass per day leads to rapid changes in eating behaviour, a reduction of food intake and subsequent loss of adipose mass and body weight64,66. Beneficial metabolic and endocrine effects are also observed, among them improvement of hyperinsulinaemia, hyperlipidaemia and liver steatosis as well as resolved central hypogonadism with onset of puberty, as seen by the induction of gonadotropin secretion and menarche126. For example, a decrease in liver lipid content can be observed as early as 3 days after onset of therapy126. After its discovery in 1994, leptin was the big hope for the treatment of common obesity127. Unfortunately, exogenous administration of leptin in patients with common, polygenic obesity had limited efficacy in clinical studies127,128.
In 2014, the FDA approved metreleptin as an orphan drug for the treatment of generalized lipodystrophy, a condition characterized by the absence or loss of body adipose tissue and, in consequence, very low levels of leptin129. Comparable to patients with congenital leptin deficiency or dysfunction, patients with generalized lipodystrophy show dramatic metabolic improvements under leptin substitution129. Of note, metreleptin has also been used to treat patients with anorexia nervosa, an eating disorder characterized by hypoleptinaemia130,131. The short-term off-label approach demonstrated beneficial cognitive, emotional and behavioural effects. These findings demonstrate that a protein that is relevant in obesity can have major effects in conditions with disordered body weight regulation or adipose tissue development.
Adverse effects of metreleptin treatment include the development of anti-leptin antibodies, which might have a neutralizing effect, and an elevated risk of lymphoma; three patients developed T cell lymphoma during therapy129. Leptin was shown to exert pro-cancer effects via the activation of pro-proliferative or anti-apoptotic pathways132. By contrast, patients with lipodystrophy might have a predisposition to lymphoma. Future studies are needed to establish a causal connection between leptin substitution therapy and lymphoma development.
Considering that most monogenic obesity traits finally converge at the central energy balance regulating MC4R pathway, treatment with MC4R agonists is a reasonable approach that might reduce food intake133,134. However, previous pharmacological attempts have failed due to lack of effect or severe adverse effects, in particular cardiovascular effects99,134.
In 2016, a milestone was reached in the treatment of monogenic obesity with the introduction of a novel MC4R agonist setmelanotide133. After the first description of POMC deficiency86, an MC4R agonist that could mimic the POMC derivative α-MSH was speculated to have the potential to decrease obesity in patients with POMC deficiency. A first pharmacological study conducted in healthy volunteers with overweight or obesity revealed that treatment with a synthetic MC4R agonist caused hypertension134. In a phase II trial in 2016, a new MC4R agonist named setmelanotide exerted beneficial effects in two patients with POMC deficiency; treatment was associated with a reduction in hunger and food intake and substantial weight loss, without an influence on blood pressure133. No adverse events were reported. Of note, skin tone and the colour of naevi darkened and hair colour changed from red to dark brown133 due to cross-reactivity of the compound with melanocortin 1 receptor (MC1R). During a period of 46 months, no malignant skin alterations were recorded135. Regular skin examinations are crucial, taking into account that specific variants in MC1R predispose to melanoma136.
Since this first report, setmelanotide has been investigated additionally in patients with deficiencies in the central leptin–melanocortin pathway, namely leptin receptor deficiency and MC4R deficiency, showing overall beneficial results. However, for six heterozygous carriers of pathogenic variants in MC4R, the weight effect associated with setmelanotide was rather subtle and comparable to the weight loss observed in control individuals with obesity who also took the drug137. The effect of setmelanotide was superior in patients with POMC deficiency compared with its effect in patients with LEPR deficiency. In a phase III trial, the majority (80%) of ten patients with POMC deficiency and 45% of 11 patients with LEPR deficiency lost at least 10% of body weight after approximately 1 year138. Phase III trials including patients with MC4R variants are currently ongoing.
In 2020, setmelanotide received FDA approval for chronic weight management in adult and paediatric patients aged 6 years and older with obesity due to POMC, PCSK1 or leptin receptor deficiency139. The EMA approval followed in 2021 for the same age range and indications.
Setmelanotide is being evaluated in phase II and phase III trials (for example, NCT03013543, NCT02311673, NCT05093634 (EMANATE) and NCT04963231 (DAYBREAK)) as a treatment option in many other genetic defects in the MC4R pathway. The drug is also being evaluated in patients with syndromic obesity (for example, Bardet–Biedl syndrome140,141 and Alström syndrome), as well as chromosomal rearrangement of the 16p11.2 locus, SH2B1, CPE or SRC1 variants, heterozygous variants of monogenic obesity, and also in patients with leptin deficiency who are unresponsive to leptin treatment139. Beyond these defined monogenic and syndromic traits, patients with obesity secondary to hypothalamic damage due to tumours or trauma might benefit from this treatment option (NCT04725240), provided the MC4R neurons are intact. Whether patients with common polygenic obesity might benefit from treatment with a MC4R agonist on the long term is questionable at this point137,142.
Interestingly, setmelanotide has been used in a patient with partial lipodystrophy who developed neutralizing antibodies under metreleptin treatment143. A slight decrease in hunger scores as evaluated by questionnaires was reported, but no other metabolic benefits. This finding underlines that leptin exerts its beneficial function on metabolism by central and peripheral modes of action that cannot be mimicked by MC4R agonism. As a side note, MC4R is not only highly expressed on neurons but also on astrocytes, and its activation has potent anti-inflammatory and neuroprotective effects144. Increased astrocytic MC4R expression was observed in active lesions in patients with multiple sclerosis144. In vitro, setmelanotide showed robust anti-inflammatory effects in astrocytes and promoted an anti-inflammatory phenotype in macrophages144. Therefore, targeting the MC4R might provide a potential strategy to delay or stop inflammation-associated neurodegeneration.
Based on the success of GLP1 agonism in adolescents with common obesity145, studies were performed to investigate if it might be beneficial in patients with monogenic obesity. Indeed, in case reports, treatment with liraglutide induced weight loss (adipose mass and lean mass) and improved metabolic parameters in individuals with pathogenic variants of MC4R146,147,148.
Innovative treatment approaches
Enormous knowledge has accumulated about the concerted regulation of glucose homeostasis, hunger and satiety, energy expenditure and eating behaviour, and the respective underlying molecular mechanisms149. This knowledge has led to the development of some innovative treatment approaches for both common polygenic obesity and obesity syndromes.
Most single-hormone targeting approaches for the treatment of polygenic obesity reveal a limited efficacy of less than 5% and rarely more than 10% body weight reduction149. Thus, it was logical to analyse if the drugs perform better when administered together than when administered singly. Indeed, several studies in rodent models revealed that combination therapies can achieve metabolic improvements superior to the effect of single hormone therapies149. Based on this premise the principle of unimolecular polypharmacology was developed.
The journey started with the development of a dual agonist unifying the features of GLP1 and glucagon for the treatment of glucose intolerance and obesity149,150. GLP1 exerts anti-diabetic actions, whereas glucagon is known to have acute hyperglycaemic effects, making this combination seem not very intuitive. However, glucagon has several additional functions; for example, inhibition of lipid synthesis and stimulation of lipolysis, inducing browning in adipose tissue that increases energy expenditure, and decreasing food intake149. Indeed, a rationally designed dual GLP1 and glucagon receptor agonist normalized glucose tolerance and improved obesity in mice receiving a high-fat diet150, with improved efficacy relative to treatment with the individual single hormones. Since that time a plethora of different combinations of dual and even triple agonists have been designed and some of them are currently being evaluated in clinical studies for T2DM and obesity149,151. Based on the results of phase III studies152,153,154,155,156, tirzepatide (a dual glucose-dependent insulinotropic polypeptide and GLP1 receptor agonist) has received FDA approval for the treatment of adults with T2DM. The compound induces clinically relevant weight loss in patients with T2DM. Remarkably, in individuals with overweight or obesity without T2DM, tirzepatide treatment resulted in a weight loss of 22.5%157.
Other approaches in preclinical development combine GLP1R agonists with nuclear hormones such as oestrogen or thyroid hormone, thereby restricting the nuclear hormone cargo to act favourably on the cells expressing GLP1R158. Patients with pathogenic variants in the leptin–melanocortin pathway downstream of the MC4R or with homozygous, heterozygous and compound heterozygous variants in MC4R who are not suitable for treatment with setmelanotide, might benefit from these developments in the area of unimolecular polypharmacology. For an excellent summary on advances in anti-obesity drug discovery see ref.159.
Future innovative therapies
Besides novel pharmacotherapies, other types of innovative therapeutic approaches might find their path into the area of obesity and body weight regulation160 (Box 4). Patients with monogenic forms of obesity might benefit from novel induced pluripotent stem cell (iPSC) technologies and CRISPR-mediated gene editing. In 2006, iPSCs were first produced from mouse fetal and adult fibroblasts161. Subsequently, the reprogramming of somatic cells into pluripotent cells rapidly succeeded in human cells162. Although hampered by the inherent risk factors of tumorigenicity and immunogenicity, iPSCs have enormous clinical potential163. In the context of obesity, iPSCs are useful as in vitro disease models to study the influence of gene variants in different cell types. For example, hypothalamic-like neurons were generated from iPSCs of patients with polygenic, severe obesity (BMI >50 kg/m²)164. Capable of neuropeptide secretion and responsive to leptin and ghrelin, they retained the typical disease features, such as dysregulated cellular respiration and molecular signatures related to metabolic disease, and can therefore be used to study the role of certain gene variants, but also gene–environment interactions164.
The ultimate aim would be to functionally repair defective gene variants that lead to monogenic obesity by CRISPR–Cas9-mediated gene editing. This approach might be considered as a last resort in patients who are not suitable for pharmacotherapy and in whom other treatment approaches have failed. Up to now, two strategies are conceivable165. First, delivery of CRISPR tools into target cells ex vivo and subsequent transplantation of engineered cells back into the patient. This approach has been useful in haematological disorders and in cancer immunotherapy, but it is not suitable for many other tissue types165. To our knowledge, this option has not been investigated in the context of monogenic obesity. Second, in vivo editing, where the CRISPR cargos are injected systemically or locally. The latter approach has been applied in leptin-deficient, obese ob/ob mice using an adenoviral CRISPR system injected locally into white adipose tissue166. Although less than 2% of alleles were repaired, the production of leptin and its physiological functions, such as inhibition of food intake, were restored. Comprehensive preclinical studies are needed to bring these novel therapeutic approaches into clinical practice.
For children and adolescents with common polygenic obesity, the main focus is prevention of weight gain as early as possible. Generalized recommendations have been developed24 but their successful implementation in the general population is questionable. Once obesity has manifested in children and adolescents, it has a high likelihood of persisting into adulthood3. Hence, we need to identify children at risk of severe and progressive obesity before manifestation. For this, surveillance of individual growth data is pertinent167. Once an accelerated weight gain is noted, validated PRS can further help estimate the obesity risk. As our understanding of obesity subphenotypes advances, PRS can help tailor the components of non-pharmacological and pharmacological treatment options to individual patients to obtain maximum effectiveness in weight gain prevention or weight reduction. Improved recognition of patients with underlying medical causes of obesity such as polygenic or syndromic obesity including monogenic forms, as well as a better access to diagnostic and genetic testing is of the utmost importance. Even with current genetic diagnostic technologies, many patients with genetic obesity disorders are probably not identified77,168. Furthermore, only a minority of children who are eligible for diagnostic tests according to current guidelines have actually undergone such testing169. An urgent need exists for more personalized prevention and treatment strategies. Concepts such as nutritional and exercise genomics or metabolomic evaluations might be useful here170,171.
Novel genetic diagnostic advances hold the potential to achieve rapid diagnosis of patients with known forms of monogenic or syndromic obesity, but also give hope for the discovery of so far unknown causes of obesity. Eventually, variant detection can lead to precision medicine and personalized treatment. Early and correct diagnosis of early-onset obesity will lead to proper treatment, prevent the development of obesity sequelae, avoid failure of conservative treatment approaches and protect patients and families from stigmatization.
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The authors thank L.S. Rajcsanyi (University of Duisburg-Essen, Essen, Germany) for her help with the first version of the figure. A.H. acknowledges the support of funding from Deutsche Forschungsgemeinschaft (DFG; HI 865/2-1), the BMBF (01GS0820, PALGER2017-33: 01DH19010) and the Stiftung Universitätsmedizin Essen. A.K. acknowledges the support of grants from the DFG, KO3512/3-1 and the DFG-funded Collaborative Research Center “ObesityMechanisms” CRC1052 (no. 209933838), and the German Diabetes Association (DDG). P.F.-P. acknowledges the support of funding from Deutsche Forschungsgemeinschaft (Heisenberg professorship, project number 398707781).
A.K. provided unpaid advice to Rhythm Pharmaceuticals. The other authors declare no competing interests.
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CDC growth charts: https://www.cdc.gov/growthcharts/clinical_charts.htm
Clinical trials: https://clinicaltrials.gov/ct2/home
Confirmed genes for different complex traits: https://www.ebi.ac.uk/gwas/
OMIM database: https://www.omim.org/
WHO child growth standards: https://www.who.int/tools/child-growth-standards
- Heritability estimates
The proportion of variation that is attributable to genetic as opposed to environmental factors for a given phenotype.
- Polygenic predictor
An estimation of the genetic liability to a complex human trait using genome-wide genetic variants.
- Barker hypothesis
This hypothesis postulates that the origins of chronic diseases in adult life lie in fetal responses to the intrauterine environment.
- CRISPR-mediated gene editing
CRISPR–Cas9 enzymes were developed from a naturally occurring genome editing system, important for immune defence in bacteria, and can be used to edit parts of the genome.
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Hinney, A., Körner, A. & Fischer-Posovszky, P. The promise of new anti-obesity therapies arising from knowledge of genetic obesity traits. Nat Rev Endocrinol 18, 623–637 (2022). https://doi.org/10.1038/s41574-022-00716-0