Abstract
Objective
The objective of this study was to investigate head circumference (HC) in patients with melanocortin 4 receptor (MC4R) deficiency, the most common cause of monogenetic obesity.
Methods
Patients with (likely) pathogenic MC4R variants were included. HC, height, and weight were measured, and BMI and standard deviation score (SDS) were calculated. HC SDS was compared to the Dutch reference population. Children were matched 1:1 to a control group with common obesity.
Results
Children with MC4R deficiency (n = 63, mean age, 10.32 years) had significantly larger HC (mean, +1.73 SDS) compared to the reference population (0 SDS; p < 0.001) and controls (+1.22 SDS; p = 0.009). In adults (n = 13), HC (median, + 0.86 SDS) did not differ from the reference population (0 SDS; p = 0.152). Macrocephaly (HC ≥ 2 SDS) was present in 43%, 25%, and 23% of pediatric patients with MC4R deficiency, controls, and adult patients, respectively. Children with MC4R deficiency were taller than controls (+1.00 SDS vs. +0.42 SDS; p = 0.016), with similar BMI (+3.99 SDS vs. +3.75 SDS; p = 0.157). HC SDS was associated with height SDS (R 2, 0.22; p < 0.001) and homeostatic model assessment of insulin resistance (correlation coefficient, 0.542; p < 0.05).
Conclusions
Macrocephaly is a common feature of patients with MC4R deficiency. We recommend measuring HC in patients suspected for genetic obesity, as it can be a clue for MC4R deficiency.
Study Importance.
What is already known?
Melanocortin 4 receptor (MC4R) deficiency is the most common cause of monogenetic obesity. Although macrocephaly is a diagnostic feature of other types of genetic obesity, such as 16p11.2 deletion syndrome, head circumference (HC) has not yet been examined systematically, to our knowledge, in patients with MC4R deficiency.
What does this study add?
This study shows that large HC is a common feature of MC4R deficiency, with high prevalence of macrocephaly.
How might these results change the direction of research or the focus of clinical practice?
We recommend including HC measurement in the diagnostic work‐up of pediatric patients suspected for genetic obesity, as it can be a clue for MC4R deficiency.
INTRODUCTION
Obesity is a highly prevalent and complex disease characterized by excessive body fat accumulation. Obesity often has a multifactorial cause such as common genetic factors, dietary factors, insufficient physical activity, or use of weight‐inducing medication. However, in a minority of patients, obesity has an underlying genetic cause [1]. Identification can be difficult as genetic obesity disorders encompass a heterogeneous group of conditions and phenotypes, classically divided into nonsyndromic and syndromic genetic obesity. It is important to identify the molecular defect in these patients as early as possible because they are often refractory to conventional lifestyle intervention and need specific treatment in specialized centers [2]. However, novel pharmacotherapeutic treatment options have become available for genetic obesity [2, 3]. Because genetic obesity disorders are rare, they can be challenging to diagnose. The majority of patients with genetic obesity are probably still undiagnosed, as has been shown for leptin receptor deficiency, which is much more prevalent in Europe (n = 998 predicted patients) than currently known in literature (n = 21 patients) [4]. Therefore, more knowledge on the clinical phenotype and core features is needed.
One of the most common types of nonsyndromic monogenetic obesity is melanocortin 4 receptor (MC4R) deficiency [5, 6, 7]. This receptor is a key part of the leptin‐melanocortin pathway, which plays a major role in weight regulation, satiety, and energy homeostasis [8, 9]. Defects in this pathway cause the following characteristic features of monogenetic obesity: severe early‐onset obesity and hyperphagia. So far, almost 200 different (likely) pathogenic variants in MC4R have been reported [10, 11]. The severity of obesity in patients with MC4R deficiency is variable, and a distinctive clinical extended phenotype has not yet been described [12, 13]. Whereas severe early‐onset obesity and hyperphagia are indeed features of MC4R deficiency, studies have also shown that pathogenic MC4R variants can cause increased linear growth, hyperinsulinemia, and increased lean body mass [8, 11, 14, 15]. In our outpatient clinic, we noticed that patients with MC4R deficiency regularly have a large head circumference (HC). In literature, macrocephaly is described in only two cases: one with a deletion encompassing the MC4R gene, and the other with a pathogenic monoallelic MC4R variant [16, 17]. Other forms of genetic obesity such as 16p11.2 deletion syndrome are associated with increased HC [18]. Studies on clinical phenotypic features of MC4R deficiency have been scarce and only comprise small patient cohorts [15]. There is currently no evidence in literature for a relationship between HC and MC4R deficiency.
The primary aim of this study is to examine HC in a large cohort of pediatric and adult patients with MC4R deficiency in order to establish whether a larger HC is indeed a characteristic of MC4R deficiency. This may aid health care professionals in identifying patients with MC4R deficiency.
METHODS
Study design and setting
This is an observational study, conducted at the outpatient clinic of the Obesity Center Centrum Gezond Gewicht (CGG; i.e., Center for Healthy Weight). Obesity Center CGG is a nationally and internationally recognized tertiary referral center for obesity at Erasmus Medical Center (MC) in Rotterdam, the Netherlands, and is also the center of expertise for genetic obesity, which is a tertiary referral center for rare genetic obesity disorders at Erasmus MC (Departments of Pediatrics and Internal Medicine) and Amsterdam University MC (Department of Clinical Genetics). Patients are referred to this center due to the presence of severe obesity and/or suspicion of an underlying cause. This study focused on the pediatric patients (i.e., those aged <18 years). All pediatric patients who are referred to this center are asked for informed consent to participate in the data‐biobank. The clinical data of these patients were included prospectively in the Obesity Center CGG pediatric database, and analysis consisted of patients included between June 2008 and January 2024. Adult patients with MC4R deficiency were selected retrospectively from the adult outpatient clinic of the Obesity Center CGG in the same period and were included as a post hoc analysis. The study was approved by the medical ethics committee of the Erasmus MC, and written informed consent was provided by the included patients and/or their caregivers.
Study population
In this study, patients were included when they were diagnosed with MC4R deficiency, classified as either monoallelic or biallelic likely pathogenic (class 4) or pathogenic (class 5) MC4R variants according to the American College of Medical Genetics and Genomics (ACMG) guidelines [19]. Patients with no available data on HC were excluded from the analyses, as well as patients with other comorbidities or conditions that are possibly associated with macrocephaly. Nine of our pediatric patients with MC4R deficiency have been described before by Kleinendorst et al., but HC was not examined in this publication [1]. Pediatric patients were matched 1:1 to a control group based on age and sex. The control group included patients from the same pediatric outpatient clinic population with severe common/multifactorial obesity, in which no single cause of obesity was found. Patients with abnormal results of the obesity gene panel were excluded from the control group, resulting in control patients with either normal results on the obesity gene panel or no indication for genetic testing due to no early onset and/or no hyperphagia.
Data collection
The diagnostic clinical routes for pediatric and adult patients of the Obesity Center CGG have been described previously in more detail [1, 20]. In summary, they consist of outpatient clinic visits, including an intake visit performed by a physician. In the standard procedure for all patients, questionnaires on medical and family history are administered, and extensive physical examination is performed. In pediatric patients, growth charts are also assessed.
During the intake visit, anthropometric measurements are performed by doctor's assistants specialized and trained in pediatric endocrinology using standardized protocols. If it was not possible to perform anthropometric measurements during intake (e.g., telephone/web intake during the COVID‐19 pandemic), these measurements were performed during the screening visit. The screening visit is the second visit, in which extensive diagnostic testing is performed. HC (centimeters) is determined using a measuring tape by taking the average of three consecutive measurements of the largest occipitofrontal circumference. Macrocephaly was defined as HC ≥ 2 standard deviation score (SDS). Weight (kilograms) and height (centimeters) are measured rounded to the nearest decimal using a calibrated scale and a wall‐mounted calibrated stadiometer, respectively. Patients are weighed wearing light clothing and without shoes. Growth Analyser RCT version 4.1 (Growth Analyser BV) was used to calculate body mass index (BMI) and SDS of HC, weight, height, and BMI according to the Dutch National Growth Charts, which use the definition of obesity by Cole et al. [21, 22, 23]. When HC was missing at the screening and/or intake visit, we searched the medical report for other available measurements. If multiple HC measurements were available, the measurement closest to the date of the screening and/or intake visit was entered in the database. Data on the type of MC4R variant and ACMG classification were collected through genetic reports from the obesity gene panel of certified clinical genetics laboratories. The content of the obesity gene panel has been previously described in more detail and has since been frequently updated based on new scientific insights [1].
For pediatric patients, additional data were collected on presence of hyperphagia, age of onset of obesity, and presence of endocrinopathy. The presence of hyperphagia was determined by a multidisciplinary team, as described previously in more detail [1]. For a post hoc analysis, laboratory results were also collected. These results included the glucose (millimoles per liter) and insulin (picomoles per liter) levels before and after an oral glucose tolerance test (OGTT), hemoglobin A1c (HbA1c) levels (millimoles per mole), and insulin‐like growth factor‐1 (IGF‐1) SDS. The homeostatic model assessment of insulin resistance (HOMA‐IR) was calculated using the following formula: (fasting glucose in millimoles per liter × fasting insulin in milliunits per liter)/22.5.
In adults, HC, weight, and height were measured using the same protocol described previously. However, in adult patients, HC is not measured routinely at the intake visit. The medical record was searched for available measurements at adult age. Weight and height measurements from the same day as the HC or any other date within 6 months of the HC measurement were entered in the database. If measurements were available >6 months before or after the HC measurement, only height was included in the database.
Data analysis
Statistical analyses were performed using SPSS Statistics version 28.0 (IBM Corp.). Normally distributed data are presented as mean (SD), and not normally distributed data are presented as median (IQR). The primary outcome of this study is the difference in HC SDS in pediatric and adult patients with MC4R deficiency compared to the reference population from the Dutch National Growth Charts based on the last Dutch National Growth Study performed in 2009 [22]. A one‐sample t test was used to examine the anthropometric measurements of patients with MC4R deficiency compared to the reference population. For pediatric patients, we additionally compared HC SDS, height for age SDS, and BMI SDS between patients with MC4R deficiency and the control group using unpaired t tests. Possible relationships of sex, age, type of MC4R variant, height SDS, weight SDS, or BMI SDS with HC SDS of pediatric patients were assessed using independent‐sample t tests, simple and multivariable linear regression analysis, and one‐way ANOVA tests, as appropriate. A subgroup analysis regarding HC was performed for pediatric patients with monoallelic MC4R variants compared to patients with biallelic MC4R variants. Receiver operating characteristic analysis was performed post hoc.
Hyperinsulinemia has been suggested to cause taller stature in patients with MC4R deficiency [8, 14]. Okawa et al. have shown that hyperinsulinemia increases linear growth through direct effects on bone and the growth hormone–IGF‐1 axis [24]. We included a post hoc analysis in pediatric patients to investigate whether HC is also associated with hyperinsulinemia. In this post hoc analysis, possible correlations between HC SDS and glucose levels, insulin levels, HbA1c, and HOMA‐IR were examined using Spearman rank tests, corrected for BMI SDS and height SDS. A correlation coefficient with ρ ≥ 0.7 was considered a strong correlation, 0.3 ≤ ρ < 0.7 was considered moderate, and ρ < 0.3 was considered weak. Two‐sided p < 0.05 was considered statistically significant.
RESULTS
Baseline characteristics
Out of 67 pediatric patients with a (likely) pathogenic MC4R variant, 63 (94%) met the inclusion and exclusion criteria for this study and were matched to a control patient (Figure 1). Baseline characteristics are presented in Table 1. The mean (SD) age at evaluation of the patients with MC4R deficiency was 10.32 (4.52) years and 10.26 (4.62) years in the control group, and 48% were boys (n = 30 in both groups). A monoallelic MC4R variant was present in 59 (94%) patients, of which c.105C>A p.(Tyr35*), c.493C>T p.(Arg165Trp), and c.785del p.(phe262Serfs*4) were the most common variants (n = 23, n = 6, and n = 5, respectively). A biallelic MC4R variant was present in four patients (6%; n = 3 homozygous, n = 1 compound heterozygous; n = 1 boy). In the control group, 56 (89%) patients had normal results on the obesity gene panel, and 7 (11%) patients did not undergo genetic testing. There were no differences in ethnicity between the two groups (post hoc analysis, p = 0.674).
FIGURE 1.
Flowchart of the inclusion of pediatric patients with MC4R deficiency. MC4R, melanocortin 4 receptor.
TABLE 1.
Baseline characteristics of the pediatric study population.
| Children with MC4R deficiency (n = 63) | Pediatric control patients (n = 63) | p value | |
|---|---|---|---|
| Age, mean (SD), y | 10.32 (4.52) | 10.26 (4.62) | 0.937 |
| Sex, n (%), boys | 30 (47.6) | 30 (47.6) | 1.000 |
| Presence of hyperphagia, n (%) | <0.001* | ||
| Yes | 50 (79.4) | 19 (30.2) | |
| Unsure | 1 (1.6) | 2 (3.2) | |
| Age of obesity onset, n (%) | 0.014* | ||
| Younger than age 5 y | 45 (71.4) | 32 (50.8) | |
| Older than age 5 y | 7 (11.1) | 22 (34.9) | |
| Uncertain or unknown | 11 (17.5) | 9 (14.3) | |
| Monoallelic MC4R variant, n (%) | 59 (93.7) | N/A | N/A |
| c.105C>A p.(Tyr35*), class 5 | 23 (36.5) | ||
| c.493C>T p.(Arg165Trp), class 5 | 6 (9.5) | ||
| c.785del p.(Phe262Serfs*4), class 5 | 5 (7.9) | ||
| c.380C>T p.(Ser127Leu), class 4 | 4 (6.3) | ||
| c.779C>A p.(Pro260Gln), class 5 | 3 (4.8) | ||
| c.240C>A p.(Tyr80*), class 5 | 3 (4.8) | ||
| c.64A>T p.(Arg22*), class 5 | 2 (3.2) | ||
| c.215A>G p.(Asn72Ser), class 4 | 2 (3.2) | ||
| c.896C>A p.(Pro299His), class 4 | 2 (3.2) | ||
| c.902T>C p.(Ile301Thr), class 5 | 1 (1.6) | ||
| c.750_751 del (lle251Trpfs*34), class 5 | 1 (1.6) | ||
| c.153 del p.(Phe51Leufs*2), class 5 | 1 (1.6) | ||
| c.521G>A p.(Trp174*), class 4 | 1 (1.6) | ||
| c.449 C>T p (Thr150LLe), class 4 | 1 (1.6) | ||
| c.63_534del p.(Leu211Metfs*6), class 5 | 1 (1.6) | ||
| c.496G>A p.(Vall166lle), class 5 | 1 (1.6) | ||
| c.878G>A p.(Cys293Tyr), class 4 | 1 (1.6) | ||
| c.784T>C p.(Phe262Leu), class 4 | 1 (1.6) | ||
| Biallelic MC4R variant, n (%) | 4 (6.3) | ||
| c.785 del p.(Phe262Serfs*4), class 5 | 2 (3.1) | ||
| c.216C>A p.(Asn72Lys), class 5 | 1 (1.6) | ||
| c.181G>T p.(Glu61*), c.(?_1)_(*1 +?)del p.(?) | 1 (1.6) | ||
| Endocrinopathy, n (%) | 5 (7.9) | 5 (7.9) | 0.700 |
| Hashimoto disease | 2 (3.1) | 0 (0.0) | |
| Central hypothyroidism | 2 (3.1) | 3 (4.8) | |
| Thyroiditis (not specified) | 1 (1.6) | 0 (0.0) | |
| Idiopathic partial growth hormone deficiency | 0 (0.0) | 1 (1.6) | |
| Pan hypopituitarism after craniopharyngioma | 0 (0.0) | 1 (1.6) |
Abbreviations: MC4R, melanocortin 4 receptor; N/A, not applicable.
p < 0.05.
Anthropometric measurements
The pediatric patients with MC4R deficiency had a significantly larger mean HC of 1.73 SDS compared to the reference population (95% confidence interval [CI]: 1.44 to 2.01; p < 0.001) and the control group (mean HC 1.22 SDS, SD 1.00, 95% CI: −0.88 to −0.13; p = 0.009: Figure 2, Table 2). Macrocephaly was present in 27 pediatric patients with MC4R deficiency (43%) compared to 16 control patients (25%; p = 0.039). In the control group, HC SDS did not differ between patients with and without genetic testing (p = 0.769). The area under the curve for HC is 0.619 (95% CI: 0.52 to 0.72). The pediatric patients with MC4R deficiency had a significantly taller height compared to the control group (95% CI: −1.04 to −0.11; p = 0.016; Table 2). BMI was not significantly different (BMI SDS 3.99 and 3.75, respectively; p = 0.159; Table 2).
FIGURE 2.
Whisker‐box plot of head circumference (HC) standard deviation score (SDS) in patients with MC4R deficiency (red) and controls with obesity (blue). Green area from −2 to +2 SDS = normal range of HC. MC4R, melanocortin 4 receptor. [Color figure can be viewed at wileyonlinelibrary.com]
TABLE 2.
Anthropometric measurements for pediatric patients with MC4R deficiency (n = 63) and control patients (n = 63)
| Children with MC4R deficiency a | Pediatric control patients | p value | |
|---|---|---|---|
| Macrocephaly (HC ≥ 2 SDS), n (%) | 27 (42.9) | 16 (25.4) | 0.039 |
| HC SDS, mean (SD) | 1.73 (1.14)** | 1.22 (1.00)** | 0.009 |
| Height SDS, mean (SD) | 1.00 (1.13)** | 0.42 (1.45)* | 0.016 |
| Weight SDS, mean (SD) | 4.34 (1.39)** | 3.69 (1.31)** | 0.008 |
| BMI SDS, mean (SD) | 3.99 (0.96)** | 3.75 (0.93)** | 0.159 |
Abbreviations: HC, head circumference; MC4R, melanocortin 4 receptor; SDS, standard deviation score.
For height, weight, and BMI, n = 61 (n = 2 missing).
p < 0.05, compared to the national reference population (one‐sample t test).
p < 0.001, compared to the national reference population (one‐sample t test).
Factors associated with HC in pediatric patients
No association was found between age and HC SDS in pediatric patients with MC4R deficiency (R 2 0.019; p = 0.28; Figure 3A) and the control group (R 2 0.015; p = 0.34). In patients with MC4R deficiency, female sex was associated with having a larger HC SDS (female mean HC SDS 2.07, male mean HC SDS 1.35, 95% CI: −1.26 to −0.17; p = 0.012). This difference was not present in the control group (female mean HC SDS 1.40, male mean HC SDS 1.02, 95% CI: −0.88 to 0.12; p = 0.13). Comparing all the individual types of MC4R variants, no association between variant and HC was found (p = 0.482). For the other anthropometric measurements, a significant association with HC was found for height in both groups (MC4R deficiency R 2 0.215, p < 0.001; control group R 2 0.263, p < 0.001; Figure 3B), but this was not observed for BMI (MC4R deficiency R 2 0.038, p = 0.130; control group R 2 0.033, p = 0.155; Figure 3C).
FIGURE 3.
Relationship between head circumference SDS and (A) age (years), (B) height SDS, and (C) BMI SDS in patients with MC4R deficiency and the control group. MC4R, melanocortin 4 receptor; SDS, standard deviation score. [Color figure can be viewed at wileyonlinelibrary.com]
A multiple regression analysis was performed to explain HC from height SDS and BMI SDS in patients with MC4R deficiency (R 2 0.224, F 8.37; p < 0.001). Height SDS remained a significant predictor of HC (coefficient 0.46, SE 0.12; p < 0.001), whereas BMI was not a significant predictor (coefficient 0.10, SE 0.14; p = 0.45). Similar results were seen in the control group (R 2 0.273, F 11.26; p < 0.001; height SDS only significant predictor of HC).
Biallelic versus monoallelic MC4R variants
The group of pediatric patients was divided into two subgroups based on the presence of a monoallelic or biallelic MC4R variant. In both groups, there was one patient with missing measurements for height and weight. Patients with a biallelic MC4R variant (n = 4) had a median (IQR) HC of 2.67 SDS (2.34 to 3.19), and patients with a monoallelic variant (n = 59) had a median HC of 1.63 SDS (−0.77 to 4.43). The patients with a biallelic variant tended to have a larger HC (mean difference −1.06, 95% CI: −2.22 to 0.10; p = 0.072). Median height of the three biallelic patients was 0.85 SDS (0.14 to 2.16), and their median BMI was 4.33 SDS (3.99 to 4.55). Median height of the monoallelic patients (n = 59) was 0.96 SDS (−1.87 to 4.21), and their median BMI was 3.93 SDS (1.80 to 7.18). All adult patients had a monoallelic MC4R variant.
Post hoc analysis on glucose tolerance and insulin resistance in pediatric patients
The results of the laboratory tests are shown in Table 3. There were no differences in fasting glucose and insulin levels between the pediatric patients with MC4R deficiency and the control group (p values, respectively, 0.270 and 0.404; Table 4). Also, 2 h after the OGTT, there were no differences in glucose and insulin levels (p values, respectively, 0.370 and 0.914; Table 4). HbA1c was significantly higher in the patients with MC4R deficiency (36 mmol/mol) compared to the control group (33 mmol/mol; p = 0.005; Table 4). HOMA‐IR was comparable in both groups (3.68 vs. 3.37; p = 0.571), as well as IGF‐1 SDS (0.41 vs. 0.32; p = 0.851; Table 4).
TABLE 3.
Laboratory results for pediatric patients with MC4R deficiency (n = 63) and control patients (n = 63)
| n | MC4R deficiency | n | Control patients | p value | |
|---|---|---|---|---|---|
| Fasting glucose, median (IQR), mmol/L | 58 | 4.8 (4.48–5.10) | 62 | 4.9 (4.60–5.30) | 0.270 |
| Glucose after 2 h, median (IQR), mmol/L | 48 | 6.5 (5.6–7.1) | 55 | 6.7 (6.0–7.3) | 0.370 |
| Fasting insulin, median (IQR), pmol/L | 54 | 122 (77–228) | 59 | 110 (55–174) | 0.404 |
| Insulin after 2 h, median (IQR), pmol/L | 46 | 550 (305–1186) | 53 | 577 (378–1036) | 0.914 |
| HbA1c, median (IQR), mmol/mol | 54 | 36 (33.0–37.3) | 53 | 33 (31.5–36.0) | 0.005* |
| HOMA‐IR, median (IQR) | 54 | 3.68 (2.16–7.59) | 58 | 3.37 (1.93–5.52) | 0.571 |
| IGF‐1, median (IQR), nmol/L | 55 | 26.7 (20.4–46.9) | 59 | 29.2 (22.7–46.9) | 0.569 |
| IGF‐1 SDS, median (IQR) | 55 | 0.41 (−0.50–1.02) | 59 | 0.32 (−0.53–1.39) | 0.851 |
Abbreviations: HbA1c, hemoglobin A1c; HOMA‐IR, homeostatic model assessment of insulin resistance; IGF‐1, insulin‐like growth factor‐1; MC4R, melanocortin 4 receptor; SDS, standard deviation score.
p < 0.05.
TABLE 4.
Correlation coefficients for HC SDS in pediatric patients with MC4R deficiency and the control group.
| HC SDS | Height SDS | BMI SDS | |
|---|---|---|---|
| HOMA‐IR | |||
| MC4R deficiency | 0.542* | 0.083 | 0.129 |
| Control group | 0.044 | 0.074 | 0.206 |
| Fasting insulin, pmol/L | |||
| MC4R deficiency | 0.546* | 0.126 | 0.144 |
| Control group | 0.018 | 0.071 | 0.219 |
| Insulin after 2‐h OGTT, pmol/L | |||
| MC4R deficiency | 0.423* | 0.268 | −0.098 |
| Control group | −0.016 | 0.021 | 0.142 |
| IGF‐1 SDS | |||
| MC4R deficiency | 0.134 | 0.079 | −0.042 |
| Control group | −0.057 | 0.303* | −0.113 |
Note: HOMA‐IR was corrected for BMI and height SDS. Height SDS was corrected for BMI SDS, and BMI SDS was corrected for height SDS.
Abbreviations: HOMA‐IR, homeostatic model assessment of insulin resistance; IGF‐1, insulin‐like growth factor‐1; MC4R, melanocortin 4 receptor; OGTT, oral glucose tolerance test; SDS, standard deviation score.
p < 0.05.
HOMA‐IR showed a moderate positive correlation with HC SDS (ρ of 0.495; p < 0.001) in patients with MC4R deficiency, which was not observed in the control group. Also, fasting insulin levels and insulin levels 2 h after the OGTT were positively correlated with HC SDS in patients with MC4R deficiency (both moderate; ρ of 0.540 with p < 0.001 and ρ of 0.531 with p < 0.001, respectively), whereas this was not seen in the control group. There was no correlation between IGF‐1 SDS and HC SDS in the MC4R group and the control group. Scatterplots of these correlations with HC SDS are shown in Figures S1 through S4. HOMA‐IR, fasting insulin, and insulin 2 h after the OGTT were not correlated with height SDS and BMI SDS in both patients with MC4R deficiency and the control group. Only IGF‐1 SDS was significantly correlated with height SDS in the control group (weak‐to‐moderate correlation with ρ of 0.303; p = 0.021; Figure S5).
When HOMA‐IR was added to the earlier performed multiple regression analysis with height SDS and BMI SDS, a stronger prediction for HC SDS was seen in the patients with MC4R deficiency (R 2 0.474, F 15.02; p < 0.001) compared to the control group (R 2 0.288, F 7.29; p < 0.001).
Post hoc analysis on adult patients with MC4R deficiency
Out of 36 adult patients with MC4R deficiency, 13 patients (36%) had a measurement of HC available and were therefore included in this substudy. All patients were female (100%), and they had a median (IQR) age of 36.31 (26.18–46.94) years. All patients had a monoallelic MC4R variant (100%), of which c.105C>A p.(Tyr35*) was the most common (n = 5; Table S1). In adult patients with MC4R deficiency, the median HC SDS was 0.86 (−2.27 to 3.42, 95% CI −0.30 to 1.70; p = 0.152). Macrocephaly was present in three adult patients (23%). Median height of the adult patients was −0.81 SDS (−4.54 to 2.27, 95% CI −1.79 to 0.29; p = 0.141).
DISCUSSION
In this study, we showed that pediatric patients with MC4R deficiency have a significantly larger HC (mean, +1.73 SDS) compared to the Dutch reference population and the control group with common obesity. Macrocephaly was observed in 43% of the pediatric patients, versus 25% in the control group. Interestingly, a larger HC was not observed in adult patients with MC4R deficiency, although 23% still had macrocephaly. Additionally, pediatric patients with MC4R deficiency had a significantly taller height.
This is the first study, to our knowledge, to investigate HC in patients with monogenetic obesity caused by MC4R deficiency. Current literature also lacks HC data for other types of monogenetic obesity such as leptin (receptor), proopiomelanocortin (POMC), and proprotein convertase 1 (PCSK1) deficiency. However, HC measurement is part of standard dysmorphology examination by clinical geneticists. A larger HC was previously described in patients with 16p11.2 deletion syndrome, in which they had a mean HC z score of +1.16 compared to the general population (95% CI: 0.61 to 1.71; p < 0.001) [25]. In another study regarding 16p11.2 deletion syndrome, similar results were shown, and 36% of the patients had macrocephaly [26]. A systematic review by Kaur et al. identified macrocephaly in seven out of seventy‐nine different genetic syndromes that are related to obesity [27]. Just like overweight and obesity, macrocephaly is a common condition in the general pediatric population, with reported prevalence up to 5% [28]. However, the percentage of patients with macrocephaly is significantly higher in both of our cohorts of patients with MC4R deficiency, as well as controls. This might explain why the area under the curve was 0.619 in our post hoc receiver operating characteristic analysis, showing that HC is, in fact, a discriminator between these two groups but that the model did not yet reach excellent discrimination.
Macrocephaly has a broad differential diagnosis, with causes typically arising from excessive growth of brain tissue, bone, or fluid (cerebrospinal fluid or blood). In 16p11.2 deletion syndrome, the enlarged HC is linked to increased intracranial volume, whereas 16p11.2 duplication results in a smaller HC and smaller brain volume [29]. The mechanism behind macrocephaly in MC4R deficiency remains unknown. However, a study by Horstmann et al. found that female patients with a common MC4R variant (rs17782313) had significantly increased gray matter volumes in specific brain areas, with a greater effect in those with biallelic variants [30]. This poses the question of whether increased gray matter volume is the reason for increased HC in MC4R deficiency. However, brain structure in other MC4R variants has not yet been examined, to our knowledge.
We observed that patients with biallelic MC4R variants tend to have a larger HC than patients with monoallelic variants. Previous research has shown similar results for BMI and body composition, concluding that patients with biallelic MC4R deficiency showed a more severe phenotype [8]. Our results suggest a potential allele‐dosage effect on HC.
Surprisingly, adult patients with MC4R deficiency did not show a significant increase in HC, although nearly one‐quarter still had macrocephaly. However, these findings should be interpreted cautiously due to the small sample size of adult patients (n = 13, all female). These results might imply that head growth accelerates during childhood and normalizes in adulthood. It would be interesting to investigate sex‐specific differences in HC, as girls in our pediatric cohort tended to have a larger HC.
A possible explanation of accelerated growth could be the effect of hyperinsulinemia, which has been suggested to cause taller stature in MC4R deficiency [8, 14]. In order to explore predictors of accelerated HC growth in MC4R deficiency, we conducted a post hoc analysis on HOMA‐IR, insulin, and IGF‐1 in pediatric patients. Research on insulin parameters in MC4R deficiency is limited and often comprises small sample sizes [11]. A previous study showed higher HOMA‐IR levels in 12 children with MC4R deficiency compared to 127 children with nongenetic early‐onset obesity [31]. Other studies have shown higher fasting insulin levels in children with MC4R deficiency compared to controls, without an underlying genetic cause for obesity [8, 14]. In our cohort, no statistical differences in HOMA‐IR, insulin levels, and IGF‐1 were found between the patients with MC4R deficiency and the control group, consistent with a small case–control study by Volbach et al. [15]. However, we did find associations of HOMA‐IR and fasting and 2‐h insulin levels with HC SDS in children with MC4R deficiency that were not present in the control group. Interestingly, these parameters were not linked to height SDS, aligning with a previous study that found no links among insulin parameters, advanced bone age, and height [32].
HC strongly correlates with height and weight in the general pediatric population, particularly during infancy and adolescence [33]. Therefore, obesity itself could also contribute to the larger HC observed in our study. To our knowledge, there are no other studies yet that have described HC in larger groups of children with multifactorial obesity. The mean HC of our control group was 1.21 SDS, which is significantly larger compared to the Dutch National Growth Charts. However, in our cohort, HC SDS was not correlated with BMI SDS, suggesting an effect independent of BMI.
We found a positive association between HC SDS and height SDS in the patients with MC4R deficiency (R 2 0.215) and the control group (R 2 0.263), explaining 21% to 27% of the variation in HC. However, 73% to 79% of the variation remains unexplained. In the post hoc analysis, adding HOMA‐IR to the multiple linear regression analysis increased the R 2 considerably in the patients (R 2 0.473), whereas it decreased slightly for the control patients (R 2 0.248). This supports the theory that hyperinsulinemia might contribute to the enlargement of HC in patients with MC4R deficiency.
In current literature, data regarding cognitive function and behavior has only been reported in small numbers of patients with MC4R deficiency [11]. It remains unclear whether the enlarged HC in MC4R deficiency is associated with behavior or neurodevelopmental disorders [11]. In 16p11.2 deletion syndrome, large head size has been linked to accelerated neuronal maturation and impaired neuronal migration, which are also associated with behavioral challenges and autism [34]. This raises the question of whether similar traits might be part of the phenotype of MC4R deficiency.
This study has several strengths and limitations. A limitation is that measurement of HC can be subjective, and not all the HC measurements were performed at our outpatient clinic. A total of 20% were retrieved from the medical records. Nevertheless, all measurements were performed by medical specialists, either pediatricians or clinical geneticists. Unfortunately, we had too many missing HC measurements of parents to effectively examine familial influence on HC. In general, it is challenging to find a good control group of pediatric patients with early‐onset common obesity. We were fortunate to match patients 1:1 from our database, all from the same tertiary referral center, excluding patients with abnormal obesity gene panel results. The biggest strength of our study is our sample size. Genetic obesity is a rare disease, making it challenging to capture phenotypic variation. To our knowledge, this is one of the biggest cohorts of patients with MC4R deficiency until now.
Further research with a larger, international cohort of pediatric and adult patients with (biallelic) MC4R variants is needed for more definitive conclusions. Future research should be longitudinal, with sequential measurements of HC, bone age, and insulin parameters to provide deeper insight into their relationship. Familial influence should be examined, and extensive genetic testing should be conducted. Future studies should also include radiological examination and systematic cognitive assessment to explore the relationship between MC4R deficiency and behavioral traits and to further unveil the complete phenotype of this condition.
CONCLUSION
In conclusion, pediatric patients with MC4R deficiency have a significantly larger HC and a high prevalence of macrocephaly compared to the Dutch reference population and matched controls with obesity. This is partly attributed to their taller height and insulin resistance, although the exact mechanism requires further study. We recommend measuring HC in patients suspected of genetic obesity, as it can indicate genetic analysis of MC4R and have significant impact on treatment strategies.
AUTHOR CONTRIBUTIONS
Eline E. P. L. van der Walle, Cornelis J. de Groot, Hester de Klerk, and Erica L. T. van den Akker were involved in the conception and design of the work. Eline E. P. L. van der Walle, Cornelis J. de Groot, and Hester de Klerk were involved in the acquisition, analysis, and interpretation of the data and drafted the work. Lotte Kleinendorst, Mila S. Welling, Ozair Abawi, and Renate E. H. Meeusen made substantial contributions to the acquisition and interpretation of the data and critically revised the work. Mariëtte R. Boon, Elisabeth F. C. van Rossum, Mieke M. van Haelst and Erica L. T. van den Akker made substantial contributions to the interpretation of the data and critically revised the work. All authors gave final approval for the version to be published.
CONFLICT OF INTEREST STATEMENT
The institution of Eline E. P. L. van der Walle, Cornelis J. de Groot, Mila S. Welling, Erica L. T. van den Akker, and Elisabeth F. C. van Rossum has received funding for clinical trial research from Rhythm Pharmaceuticals, Inc. The current study is not linked to this study. Mariëtte Boon and Elisabeth F. C. van Rossum receive personal royalties from Ambo Anthos for the lay book Fat: the Secret Organ. Elisabeth F. C. van Rossum discloses payments to her institution from Dutch Obesity Academy, E‐wise, and Medscape/WebMD for presentations. Mariëtte Boon discloses payments to her or her institution for presentations from Public Eyes Communication, Obesitas Platform, SCEM, Goodlife, Eli Lilly, and MedOnline and travel payments from Rhythm Pharmaceuticals. Cornelis J. de Groot received speaker fees from Rhythm Pharmaceuticals. The other authors declared no conflicts of interest.
Supporting information
Data S1. Supporting Information.
ACKNOWLEDGMENTS
We would like to thank all our patients and their caregivers for participating in our scientific research. We also want to thank the members of our team, especially Esther Hofland for her valuable role in coordinating the logistics of this study, and Marloes Vos, data manager of the Obesity Center CGG. Requests for access to anonymized data can be submitted to the corresponding author.
van der Walle EEPL, de Groot CJ, Kleinendorst L, et al. Unraveling the relationship between head circumference and MC4R deficiency from infancy to adulthood: a case–control study. Obesity (Silver Spring). 2025;33(5):986‐995. doi: 10.1002/oby.24263
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Associated Data
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Supplementary Materials
Data S1. Supporting Information.