Patients with Bardet-Biedl Syndrome Have Hyperleptinemia Suggestive of Leptin Resistance

Hyperleptinemia out of proportion to adiposity is found in Bardet-Biedl syndrome, consistent with the leptin resistance shown in mouse models of this ciliopathy.

Abstract

Objective:

Bardet-Biedl syndrome (BBS) is a genetically heterogeneous disorder of the primary cilium associated with obesity. In BBS mouse models, ciliary dysfunction leads to impaired leptin signaling and hyperleptinemia before obesity onset. To study the pathophysiology of obesity in BBS, we compared patients with BBS and body mass index Z-score (BMI-Z)-matched controls.

Design and Methods:

Fifty patients with BBS were matched 2:1 by age, sex, race, and BMI-Z with 100 controls. Patients with BBS and controls were compared for differences in body composition (dual-energy x-ray absorptiometry, abdominal magnetic resonance imaging), blood pressure Z-score (BP-Z; standardized for age, sex, and height), and fasting concentrations of leptin, lipids, insulin, and glucose. Patients with BBS were also compared by genotype.

Results:

Leptin, triglycerides, intraabdominal fat mass, and diastolic BP-Z were significantly greater in patients with BBS than in the controls. BBS1 (27%) and BBS10 (30%) mutations were the most prevalent. Patients with BBS10 mutations had significantly higher BMI-Z, greater visceral adiposity, and greater insulin resistance than those with BBS1 mutations.

Conclusions:

Patients with BBS had higher leptin than expected for their degree of adiposity, consistent with the notion that ciliopathy-induced leptin signaling dysfunction is associated with leptin resistance. The preferential deposition of fat intraabdominally in patients with BBS may indicate a predisposition for metabolic complications, including hypertension and hypertriglyceridemia. The observation of disparate results in the BBS10 vs. BBS1 mutation groups is the first demonstration of physiological differences among patients with BBS caused by mutations in distinct genes. These results suggest that the obesity of BBS is distinct from nonsyndromic obesity.

Syndromes that manifest obesity provide opportunities to dissect the pathophysiology of what is an epidemic. Bardet-Biedl syndrome (BBS; Online Mendelian Inheritance in Man, http://www.ncbi.nlm.nih.gov/omim/209900) is a pleiotropic, obesity-associated syndrome inherited in an autosomal recessive pattern (1). Although birth weight is usually normal, most patients with BBS develop marked obesity in childhood. Most also have a progressive rod/cone retinal dystrophy, polydactyly, developmental delay, learning disabilities, and behavioral problems. The diagnosis is made on the basis of clinical criteria (2) and is associated with mutations in at least 12 genes (BBS1-BBS12) (3–14). Most BBS genes encode proteins that are important in the formation, stability, and function of cilia (15). Although small studies have suggested that a specific class of mutations may be associated with characteristic ocular (16) or limb (17) findings, a well-defined genotype-phenotype correlation has not been established.

Severe obesity is an important cause of morbidity in many patients with BBS. Diabetes, hypertension, and cardiovascular disease have been reported in small numbers of older adults (18, 19), but there are few descriptions of the prevalence and severity of obesity or of metabolic dysfunction in cohorts of patients with BBS. A previous study of 20 patients with BBS reported a similar basal metabolic rate and energy intake when compared with body mass index (BMI)-matched controls, but the physical activity level of the patients with BBS was lower (20).

Mouse data suggest that ciliary derangements impair leptin receptor function (21, 22) and cause increased circulating leptin before the onset of obesity. However, no prior studies among patients with BBS have demonstrated leptin resistance.

We hypothesized that patients with BBS would have distinct obesity-associated physiological perturbations compared with patients with non-BBS obesity and there would be physiological heterogeneity among BBS genetic subtypes. To test these hypotheses, we evaluated 50 patients with BBS and 100 controls to characterize their body composition, fat distribution, metabolic parameters, and blood pressure. Our goals were to identify the similarities and differences of BBS-associated vs. nonsyndromic obesity and to determine whether there were distinct subphenotypes among patients with BBS caused by mutations in distinct genes.

Subjects and Methods

Recruitment

Subjects were studied at the Clinical Research Center, National Institutes of Health (NIH) in Bethesda, Maryland. Recruitment of subjects with BBS was through referrals from geneticists and genetic counselors, journal advertisements, and parent groups. The BBS diagnosis was made if a subject had at least three of the six “primary” criteria (2). Whenever possible, both parents were enrolled for mutation carrier status. The BBS protocol was approved by the NIH National Human Genome Research Institute Institutional Review Board (IRB). Healthy control subjects were matched 2:1 with the patients with BBS by age, sex, race, and BMI-Z. Control subjects were participants in other studies at NIH, including nontreatment studies on the natural history of normal weight and overweight children, endocrine studies of healthy volunteers, studies on the psychology of eating behaviors, and studies on obesity treatment. Recruitment of controls was primarily through advertisements. The controls were enrolled in protocols approved by the NIH National Institutes of Child Health and Human Development IRB. Participants or parents/guardians gave informed consent, and children assented, for these studies. Control subjects who had chronic medical illnesses, significant psychiatric disorders, recent weight loss, or recent weight-loss medication use were excluded.

Clinical and laboratory assessment

Fasting serum leptin was measured by immunoassay (Esoterix Inc., Calabasas Hills, CA). Patients with BBS ages 5–19 yr and controls had fasting serum insulin and glucose measured as described (23). Baseline indices of insulin sensitivity and estimates of insulin resistance were calculated from fasting glucose and insulin using the homeostasis model assessment [HOMA; I⁰ × G⁰/22.5 (24)]. Forty-three patients with BBS and 40 controls underwent the oral glucose tolerance test (OGTT; 1.75 g/kg, maximum 75 g) to examine glucose homeostasis.

Whole-body dual-energy x-ray absorptiometry (DEXA) was performed for bone mineral content, total lean body mass, and percentage body fat (Delphi A, version 12.4; Hologic Inc., Bedford, MA). Cross-sectional areas of the sc abdominal and total abdominal fat were measured (at L2–3 and L4–5) with magnetic resonance imaging (MRI) (25) in subjects less than 18 yr old or with computed tomography (CT) (26) in subjects 18 yr or older. Intraabdominal (visceral) adipose tissue was determined by subtracting sc from total abdominal fat. Regions of adiposity were summed to estimate sc, visceral, and total abdominal fat. The ratio of visceral to total (percentage visceral) abdominal fat was calculated.

Height was measured at 0900 h as the average of three measurements using a stadiometer; skeletal age was determined from an x-ray of the left hand and wrist (27).

BMI (kilograms per square meter) was used to calculate BMI Z-scores (BMI-Z; normalized for age and sex), defined using the U.S. Centers for Disease Control 2000 modified least mean squares method (28, 29). Because BMI-Z is only available for ages up to 20 yr, subjects older than 20 yr were included for analyses using BMI-Z calculated for age 20 yr.

Systolic and diastolic blood pressure Z-scores (BP-Z) were derived using National Heart, Lung, and Blood Institute (NHLBI) standards to normalize for age, sex, and height-Z (30). Because BP-Z is available only for ages up to 17 yr, subjects older than 17 yr were included in analyses by calculating BP-Z for age 17 yr.

Statistical analysis

Nonparametric tests were performed if nonnormally distributed data could not be normalized by transformation procedures: logarithm for skewed data and arcsin (square root) for boundary constrained data. Back-transformed values are shown in Results for ease of interpretation. Groups were compared using independent samples t test or Mann-Whitney U test for continuous variables, and χ² tests for frequencies. Analyses of covariance were used to compare the groups for differences in body composition, biochemistries, and blood pressure. Percentage body fat was adjusted for age, sex, race, and BMI-Z. Systolic and diastolic BP-Z, lipids, leptin, indices of glucose homeostasis, and measurements of sc and visceral abdominal fat were adjusted for age, sex, race, and percentage body fat. Although systolic and diastolic BP-Z were standardized for age and sex, these covariates were still included in the statistical analyses because adult-aged subjects had Z-scores calculated based on the maximum age available in the NHLBI and Centers for Disease Control Z-score calculation algorithms. Raw blood pressure values were adjusted for age, sex, race, height-Z, and percentage body fat. Nominal P values are shown in Results. To minimize the likelihood of false positives arising from multiple comparisons, we used a Bonferroni corrected P value < 0.004 for statistical significance.

Mutation analysis

Genomic DNA was isolated by standard procedure (31). Primers were designed to amplify coding exons and flanking introns of BBS1-BBS10 and BBS12. Mutation screening in BBS11 was not performed because only one family with BBS11 mutations has been reported (5). Purified PCR products were sequenced on an ABI 3100 semiautomated genetic analyzer (Applied Biosystems, Foster City, CA). Chromatograms were compared with the reference sequence with Sequencher v.4.9 software (Gene Codes Corp., Ann Arbor, MI). Frameshift and nonsense changes were considered causative, and missense mutations were considered likely causative if the common allele was evolutionarily conserved, the rare allele was absent in dbSNP (http://www.ncbi.nlm.nih.gov/projects/SNP/), and the amino acid change was in trans (assessed by testing parent DNA) to another likely causative variant. Screening of an individual was considered complete when two mutations were found in one gene; further variants in other genes were not sought.

Results

Comparison of patients with BBS and BMI-Z-matched controls

We enrolled 50 subjects with BBS, 25 males and 25 females, ages 4–61 yr (mean ± sd, 14.8 ± 11.1 yr) from 44 families. In four families, two siblings were affected, and in one family, three were affected. The 100 controls were well-matched with the BBS cohort with respect to age, sex, race, and BMI-Z (Table 1).

Table 1.

Comparison of unadjusted means between patients with BBS and BMI-Z-matched controls

Clinical features	BBS cases		Controls		P (two-tailed)
	n	Mean ± sd	n	Mean ± sd
Age (yr)	50	14.8 ± 11.1	100	15.3 ± 11.0	0.68
BMI (kg/m2)	50	31.7 ± 9.7	100	31.5 ± 8.4	0.96
BMI-Z (CDC 2000 LMS)	50	2.17 ± 0.89	100	2.10 ± 0.84	0.60
DEXA total body fat (%)	40	42.1 ± 8.5	79	39.3 ± 10.5	0.19
Ethnicity (% Caucasian)	50	98%	100	98%	1.00
Height Z-score (CDC 2000 LMS)	50	−0.03 ± 1.38	100	0.83 ± 1.30	<0.001
Sex (% female)	50	50%	100	50%	1.00
Weight Z-score (CDC 2000 LMS)	50	2.11 ± 1.08	100	2.27 ± 1.09	0.25
Abdominal visceral fat (%)	38	26.9 ± 10.4	43	19.7 ± 6.1	<0.001
Fasting glucose (mmol/liter)	46	4.72 ± 0.44	91	4.83 ± 0.5	0.08
Fasting insulin (pmol/liter)	44	135.6 ± 137.4	95	94.2 ± 65.4	0.05
HOMA-IR	44	4.92 ± 5.43	91	3.48 ± 2.73	0.07
HbA1C (%)	48	5.28 ± 0.35	69	5.42 ± 0.52	0.03
Leptin (nmol/liter)	44	2.63 ± 1.78	75	1.48 ± 1.02	<0.001
Cholesterol (mmol/liter)	48	4.14 ± 0.78	93	4.33 ± 0.91	0.28
HDL cholesterol (mmol/liter)	48	1.04 ± 0.31	93	1.14 ± 0.31	0.09
LDL cholesterol (mmol/liter)	48	2.62 ± 0.73	93	2.87 ± 0.75	0.06
Triglycerides (mmol/liter)	48	2.06 ± 1.5	93	1.27 ± 0.99	<0.001
Systolic BP-Z	49	1.17 ± 1.45	97	0.82 ± 1.23	0.12
Diastolic BP-Z	49	0.72 ± 0.80	97	0.14 ± 0.73	<0.001

HbA1C, Glycosylated hemoglobin; HDL, high-density lipoprotein; LDL, low-density lipoprotein.

Most subjects with BBS (86%) were obese; only seven had BMI below the 95th centile for age and sex. When compared with BMI-Z-matched controls, total body fat percentage was similar (Table 1); however, the patients with BBS had increased visceral adiposity compared with BMI-matched controls (P < 0.001; Table 1). The difference remained significant after adjustment for covariates (P = 0.001; Fig. 1A). The average height Z-score for patients with BBS was less than that of controls (Table 1). When divided into children (age < 18 yr) and adults (age ≥ 18 yr), children with BBS were shorter than control children (height-Z, +0.07 ± 1.30 in BBS vs. +1.08 ± 1.28 in controls; P < 0.001), whereas adults with BBS and their respective controls had heights that were not statistically different (height-Z, −0.28 ± 1.57 in BBS vs. +0.09 ± 1.09 in controls; P = 0.58). The average difference between skeletal age and chronological age for patients under the age of 18 yr with BBS was +0.3 ± 1.8 yr compared with +1.2 ± 1.4 yr for the controls (P = 0.02).

Fig. 1.

Covariate analyses of patients with BBS vs. obese control subjects (adjusted mean ± sem shown). Black bars, Controls; white bars, cases. A, Abdominal visceral fat percentage (calculated as percentage total fat at L2–3 and L4–5 measured by abdominal CT or MRI), adjusted for age, sex, race, and total body fat percentage (measured by DEXA). B, Leptin adjusted for age, sex, race, and total body fat percentage (measured by DEXA). Leptin values converted to SI units (nanomoles per liter = nanograms per milliliter × 0.0625). C, Triglycerides adjusted for age, sex, race, and total body fat percentage (measured by DEXA). D, BP-Z (standardized for age, sex, and height) adjusted for race and total body fat percentage (measured by DEXA). (For subjects more than 17 yr old, BP-Z was calculated as if age = 17 yr; therefore, adjusted for age and sex to account for further changes in BP that occur in adulthood).

Mean serum leptin concentration was nearly 2-fold higher in the BBS cohort compared with BMI-matched controls (P < 0.001; Table 1). Partial η² values were as follows: age 0.9%, sex 2.1%, race 1.3%, percentage body fat 24%, and group category (BBS vs. controls) 20%. Body fat contributed nearly one fourth of the variance in leptin concentration, whereas the other covariates together contributed less than 5%. Partial correlation analyses (adjusting for age, sex, and race) of the entire cohort, then BBS and controls separately, showed that leptin correlated with total fat mass, sc fat mass, and percentage body fat, but not with visceral fat mass or percentage visceral fat mass. Higher R² values were achieved with cubic curve equations. Subjects with BBS had leptin values that were shifted upward with steeper slopes (Supplemental Fig. 1, published on The Endocrine Society's Journals Online web site at http://jcem.endojournals.org). The leptin differences remained significant after adjustments for covariates (P < 0.001; Fig. 1B).

There was no difference in mean fasting glucose between cases and controls (Table 1). Although there was a somewhat lower glycosylated hemoglobin in subjects with BBS compared with controls (Table 1), it was not significant after correction for multiple comparisons (P = 0.31) or after adjustments for covariates (nominal P = 0.08; data not shown). HOMA of insulin resistance (HOMA-IR) was similar in subjects with BBS and controls, both with (P = 0.23; data not shown) and without adjustment for covariates (P = 0.07; Table 1). Insulin was somewhat higher in subjects with BBS compared with controls (P = 0.047; Table 1), but was not significant after multiple comparison correction (P = 0.56). Prevalence of impaired glucose tolerance (fasting glucose ≥ 5.55 mmol/liter or 2-h OGTT glucose ≥ 7.77 mmol/liter) was 10.6% of the 47 subjects with BBS who had fasting or OGTT glucose results, compared with 7.7% of controls (P = 0.54). Only one subject with BBS and one control subject had type 2 diabetes (2-h OGTT glucose ≥ 11.1 mmol/liter); both diabetic subjects were excluded from the fasting glucose, insulin, and HOMA-IR analyses.

Total, high-density lipoprotein, and low-density lipoprotein cholesterol were not different between the BBS and control groups; however, the BBS group had significantly higher mean serum triglycerides compared with controls (P < 0.001; Table 1), which remained significant after adjusting for covariates (P < 0.001; Fig. 1C).

The BBS group had similar mean systolic BP-Z compared with controls (P = 0.12; Table 1). However, mean diastolic BP-Z was higher in the BBS group compared with controls (P < 0.001) and remained significant after adjustment for covariates (P < 0.001; Fig. 1D).

After adjusting for age, sex, race, total body fat percentage, free testosterone, and estradiol, subjects with BBS continued to have significantly higher leptin (P < 0.001), diastolic BP-Z (P = 0.006), and triglycerides (P = 0.003) compared with controls, but the difference in abdominal visceral fat adiposity became nonsignificant (P = 0.06). When we dropped the 15 oldest BBS subjects (and their matched controls) so that the upper limit for age was 18 yr, the results were unchanged.

Mutation analyses of subjects with BBS

Within this cohort of 44 families with BBS, mutations in BBS1 (n = 12 families; 27%) and BBS10 (n = 13 families; 30%) were most common (Supplemental Table 1). Among those with a BBS1 mutation, nine families had probands who were homozygous, and one family contained a proband who was a compound heterozygote for c.1169T>G (p.Met390Arg) that is the most frequently detected BBS mutation (18–30%) (9). Among the families with a BBS10 mutation, six had probands who were homozygous for c.271dup (p.Cys91LeufsX5). We also observed a few families with mutations in BBS4 (4.5%), BBS5 (7%), MKKS (7%), BBS7 (7%), BBS9 (2%), and BBS12 (4.5%). Three individuals had only one mutation identified. Patient 7 had BBS1 c.1169T>G (p.Met390Arg) on one allele. Two individuals in the BBS5 subgroup had c.889G>A, (p.Asp297Asn) (patient 15), and c.619–1G>C (patient 16). In five families with BBS, no coding or splice site mutations were identified (Supplemental Table 1). Among these eight probands, there was no evidence of exonic deletion detectable by loss of heterozygosity or whole gene deletion detected on array comparative genomic hybridization analysis (data not shown). The seven nonobese subjects with BBS included two BBS1, one BBS4, two MKKS, one BBS7, and one unknown genotype.

Comparison of subjects with BBS1 and BBS10 mutations

Among the BBS subtypes, only individuals with BBS1 (n = 12) and BBS10 (n = 13) mutations had adequate sample sizes for genotype-specific comparisons. The subjects in the BBS1 group were older than those in the BBS10 group (20.2 ± 6.9 vs. 12.9 ± 13.4 yr; P = 0.001). The BMI-Z for patients with BBS1 mutations was lower than for those with BBS10 mutations (P = 0.002; Fig. 2A). Serum leptin showed a nonsignificant trend toward lower values in patients with BBS1 vs. BBS10 mutations (P = 0.09; Fig. 2B). Patients with BBS1 mutations had lower HOMA-IR compared with those with BBS10 mutations (P = 0.002; Fig. 2C), even after adjusting for age, sex, race, and percentage body fat. Subjects with BBS1 mutations had lower visceral adiposity compared with individuals with BBS10 mutations. The difference remained nominally significant (P = 0.006; Fig. 2D) after adjusting for age, sex, race, and percentage body fat. Systolic and diastolic BP-Z (standardized for age, sex, and height) were not statistically different between the BBS1 and BBS10 groups, although the BBS10 group trended toward higher diastolic BP-Z (P = 0.06). After adjustment for percentage body fat, however, the trend was abolished, with P = 0.67 and 0.33 for systolic and diastolic BP-Z, respectively. In subgroup analyses, patients with BBS1 mutations were similar to BMI-Z-matched controls for all variables, whereas the differences in visceral fat, diastolic BP-Z, leptin, and triglycerides between patients with BBS10 mutations and controls persisted.

Fig. 2.

Comparison of subjects with BBS1 mutations vs. BBS10 mutations (adjusted mean ± sem shown). Black bars, patients with BBS1 mutations; white bars, patients with BBS10 mutations. A, BMI-Z (normalized for age and sex) adjusted for age, sex, and race. (For subjects more than 20 yr old, BMI-Z was calculated as if age = 20 yr; therefore, adjusted for age and sex to account for further changes in BMI that occur in adulthood). B, Leptin adjusted for age, sex, race, and total body fat percentage (measured by DEXA). Leptin values converted to SI units (nanomoles per liter = nanograms per milliliter × 0.0625). C, HOMA-IR adjusted for age, sex, race, and total body fat percentage (measured by DEXA). D, Abdominal visceral fat percentage (calculated as percentage total fat at L2–3 and L4–5 measured by abdominal CT or MRI) adjusted for age, sex, race, and total body fat percentage (measured by DEXA).

Discussion

Bardet-Biedl syndrome is a genetic form of obesity caused by mutations in any of at least 12 genes. Discovering which of the pleiotropic manifestations in patients with BBS are shared among the genetic subtypes and which are distinct is essential to elucidate the underlying mechanisms of metabolic disturbances in this disorder. The pathophysiology of the forms of BBS may shed light on common, nonsyndromic forms of obesity. We hypothesized that patients with BBS would have distinct obesity-associated physiological perturbations compared with patients with non-BBS obesity and that there would be physiological heterogeneity within the BBS genetic subtypes. To test these hypotheses, we evaluated the obesity and metabolic profiles of 50 patients with BBS.

We found higher levels of leptin and triglycerides and greater visceral adiposity in subjects with BBS compared with controls. Secondary analyses controlling for sex steroids were also performed because nearly one third of the male subjects had hypogonadism. Although the sample size was not powered for analyses taking these covariates into account, differences either remained significant or showed trends in the same direction, suggesting that differences between BBS and controls cannot be attributed solely to sex steroid concentration differences.

In agreement with previous data (20), our study found that when patients with BBS are compared with BMI-matched controls, total body fatness is similar. Thus, BBS does not cause major derangements in nutrient partitioning. The patients with BBS in the present study were shorter than BMI-matched controls, but this may be attributed to the fact that many of this study's subjects were children who had not completed their linear growth. Grace et al. (20) found that height of 20 adults with BBS was nearly identical to that of a case control cohort. Green et al. (18) reported that the majority of 25 patients with BBS had below-average stature, but no statistical analysis was performed. Beales et al. (2) showed that overall, adults with BBS had similar heights to their sex-matched parent, but that affected individuals from families linked to BBS1 were shorter than their parents and patients from families linked to BBS2 were taller. The BBS1 and BBS2 height results in the study of Beales et al. (2) were not stratified by age, and no correction was applied for performing multiple comparisons among groups. Although the BBS subjects were shorter relative to the obese controls, their height approximated the population mean for age/sex, indicating that they are not abnormally short, but rather lack the bone age advancement and accelerated growth typically seen in obese controls. Thus, the attainment of normal stature in adulthood and comparable stature with the obese controls (who have accelerated growth but complete growth sooner due to skeletal age advancement) is not surprising.

Nonsyndromic pediatric obesity is associated with relative tall stature until adult height is attained (32). The normal average bone age in children with BBS may suggest that the growth effect of overnutrition, which is typically associated with advanced bone age, is blunted in some patients with this disorder, and one might hypothesize that, on average, children with BBS (particularly those with delayed puberty) continue their statural growth later than do comparably obese patients who do not have BBS. Murine studies suggest the possibility that elevated leptin may stimulate epiphyseal growth in obese children by directly stimulating production of type X collagen (33) as well as by stimulating the production and secretion of GH (34); however, linear growth often ceases somewhat prematurely because of advanced skeletal age (35). We suggest that additional investigation into the mechanism of statural growth retardation in patients with BBS should be undertaken to determine the mechanism of this previously unrecognized phenomenon.

We set out to understand the characteristics of obesity in patients with BBS and found they have markedly elevated serum leptin compared with matched obese controls. The high circulating leptin in the BBS cohort suggests that they may have a greater degree of leptin resistance than is found in obese individuals who do not have BBS (36). Evidence of leptin resistance has been found in the Bbs2^−/−, Bbs4^−/−, and Bbs6^−/− knockout mouse models for BBS (21). Although the administration of exogenous leptin resulted in decreased food intake and weight in wild-type mice, the effects of leptin were attenuated in Bbs4^−/− and Bbs6^−/− mice, and in Bbs2^−/− mice, completely blunted, indicating the presence of central leptin resistance (21). We conclude that patients with BBS have greater leptin resistance than would be predicted based on their BMI or fat mass, and we speculate that, as has been found for mouse models of BBS, this leptin resistance is mediated by defects in central ciliary mechanisms that affect the function of the leptin receptor or its downstream targets.

The present data also show that patients with BBS have a distribution of fat distinct from that of obese controls, with more fat stored in the visceral adipose tissue depot. Storage of fat in visceral, as opposed to sc, adipose tissue has been associated with metabolic syndrome and obesity-related complications (37–39). Consistent with the increased visceral fat is our observation of elevation of triglycerides and diastolic blood pressure compared with obese controls (37). We also observed a nonsignificant trend toward greater insulin resistance in the patients with BBS. The mechanism by which excess calories are channeled to fat storage in visceral vs. sc adipose tissue is not known. Increase in both sc and visceral adipose compartments is observed in db/db (leptin receptor-deficient) mice (40). Visceral adipose tissue is believed to produce less leptin than sc adipose tissue (41); thus, the greater intraabdominal adipose tissue found in patients with BBS would not be anticipated to explain their greater leptin concentrations. We also found that the patients with BBS1 mutations had less severe obesity than did those with BBS10 mutations. This distinction has not been previously recognized and deserves additional study because it may shed light on physiological heterogeneity among the BBS subtypes.

Surprisingly, we found that the prevalence of impaired glucose tolerance and type 2 diabetes was similar for subjects with BBS and BMI-matched controls and that HOMA-IR was similar in the groups despite the greater visceral adiposity among subjects with BBS. Our study may have been underpowered to detect a HOMA-IR difference between the BBS and control groups because of the sample size and the relatively low prevalence of type 2 diabetes among this fairly young cohort. Prior studies of patients with BBS estimated a median age of onset type 2 diabetes to be 43 yr (42). The only subject with BBS and type 2 diabetes in our cohort was 61 yr old (patient 37; Supplemental Table 1). Patients with BBS1 mutations also had significantly lower HOMA-IR and nominally significantly lower visceral adiposity than did patients with BBS10 mutations. This finding again supports the hypothesis that there is phenotypic heterogeneity among the BBS subtypes.

In summary, we found that patients with BBS had higher leptin than expected for their degree of adiposity, consistent with the notion that ciliopathy-induced leptin signaling dysfunction is associated with leptin resistance. The preferential deposition of fat intraabdominally in patients with BBS appears to indicate a predisposition for metabolic complications, including hypertension and hypertriglyceridemia. The observation of disparate results in the BBS10 vs. BBS1 mutation groups is the first demonstration of physiological distinctions among patients with mutations in distinct BBS genes. These results suggest that the obesity of patients with BBS is distinct from nonsyndromic obesity.