Lipodystrophy (LD) is a rare disease with a paucity of subcutaneous adipocytes and leptin deficiency. Patients often develop severe diabetes and, additionally, show a disturbed eating behavior with reduced satiety. The disturbed eating behavior can be restored by substitution with the leptin analog metreleptin. Long-term effects of metreleptin on resting state brain connectivity in treatment-naive patients with LD have not been assessed. In this study, resting state functional MRI scans and extensive behavioral testing assessing changes in hunger/satiety regulation were performed during the first 52 weeks of metreleptin treatment in nine patients with LD. Resting state connectivity significantly increased over the course of metreleptin treatment in three brain areas (i.e., hypothalamus, insula/superior temporal gyrus, medial prefrontal cortex). Behavioral tests demonstrated that perceived hunger, importance of eating, eating frequencies, and liking ratings of food pictures significantly decreased during metreleptin therapy. Taken together, leptin substitution was accompanied by long-term changes of hedonic and homeostatic central nervous networks regulating eating behavior as well as decreased hunger feelings and diminished incentive value of food. Future studies need to assess whether metreleptin treatment in LD restores physiological processes important for the development of satiety.

Lipodystrophy (LD) is a rare disease with a paucity of subcutaneous adipocytes and reduced blood concentrations of leptin. Several genetic mutations are known to cause partial or generalized forms of the disease. Also, cases of acquired LD have occurred (1). LD is frequently accompanied by type 2 diabetes and dyslipidemia. Leptin substitution in the form of the analog metreleptin has shown beneficial metabolic effects. In the biggest clinical trial on metreleptin treatment in LD so far, hemoglobin A1c (HbA1c) on average decreased by 1.5% and serum triglycerides (TGs) fell by >50% after 1 year of treatment (2). Additionally, a disturbed eating behavior often develops in patients with LD, with reduced satiety after food consumption, leading to an increase in meal frequency (3). Impaired eating behavior can be improved by leptin substitution, too (4). Humoral leptin crosses the blood-brain barrier by active transport in the proximity of the mediobasal hypothalamus where the blood-brain barrier is well permeable for peripheral hormones (3,5). Through receptors in the arcuate nucleus, leptin inhibits food intake by direct activation of anorexigenic cocaine- and amphetamine-regulated transcript and proopiomelanocortin neurons (6,7) as well as by inhibition of orexigenic neuropeptide Y neurons (8). In a widely accepted model of the control of eating behavior, the hypothalamus is considered to govern the homeostatic component of human eating regulation, that is, the drive to eat to meet the bodily demands for energy (9,10).

In addition, the leptin receptor is also expressed in neurons of the mesolimbic dopamine system, which is involved in the processing of motivation and reward. Here, leptin reduces dopamine signaling (11). These findings also suggest an influence of leptin on the other component contributing to the formation of human eating behavior, that is, hedonic eating, which is the drive to eat for pleasure in the absence of an energy deficit (12). Human behavioral data support the hypothesis that leptin affects both components of eating control (4,13).

Apart from the clinical need for metreleptin treatment, patients with decreased blood concentrations of leptin provide a unique model to study the central nervous effects of leptin. However, in vivo investigations of metreleptin effects on brain activation assessed with functional MRI (fMRI) have not been performed in treatment-naive patients with LD so far. Furthermore, the impact of leptin on resting state brain function, which is a useful tool for the assessment of connectivity of brain regions and long-term state changes (14), has not been investigated yet. To address these open points, the long-term effects of leptin substitution on resting state brain connectivity in treatment-naive patients with LD were assessed with task-free resting state fMRI before and at five time points over 52 weeks after initiation of metreleptin treatment. Because the anchoring of fMRI findings with behavioral results is crucial for a correct interpretation (15), all patients underwent an extensive neuropsychological assessment accompanied by metabolic tests at each study visit.

We hypothesized that with resting state fMRI, long-term increases in connectivity in both homeostatic and hedonic brain areas can be observed and that these changes are accompanied by behavioral changes, including perceived hunger/satiety and liking ratings of food pictures. We show for the first time combined long-term metreleptin treatment–related effects on behavior and resting state brain connectivity in treatment-naive patients with leptin deficiency. These findings are particularly important in view of recent successful approaches of overcoming leptin resistance (16) and hopes of using metreleptin as a therapeutic agent in obesity in the future.

Patients With LD

Nine patients with LD (seven female) eligible for metreleptin treatment at the University Hospital Leipzig participated in the MRI study. Baseline characteristics and laboratory data of included patients are summarized in Table 1. Inclusion criteria for leptin replacement were established LD, age ≥5 years at baseline, insufficiently controlled diabetes, and/or hypertriglyceridemia despite adequate antihyperglycemic and lipid-lowering medication, respectively. Exclusion criteria included pregnancy or lactation, severe renal insufficiency, active malignant disease, primary hematologic abnormalities, infectious liver disease, HIV infection, and hypersensitivity to Escherichia coli–derived proteins. All patients were metreleptin treatment–naive and consented to participating in the MRI study.

Table 1

Baseline characteristics and laboratory data of the study population

PatientPhenotype of LDMutationSexAge (years)BMI (kg/m2)Leptin (μg/L)HbA1c
(% [mmol/mol])TG (mmol/L)
Partial LMNA 23 27.4 5.3 6.4 (46) 16.3 
Partial LMNA 34 28.7 5.2 8.9 (74) 2.4 
Partial LMNA 48 27.4 9.8 6.6 (49) 2.5 
Generalized ND 16 17.4 <0.48 8.4 (68) 9.2 
Partial ND 41 30 3.6 8.0 (64) 7.9 
Generalized ND 33 20.7 <0.48 8.1 (65) 37.1 
Partial PPARγ 55 33.5 6.7 6.0 (42) 23.2 
Partial ND 39 30.8 11.2 7.6 (60) 15.6 
Partial PPARγ 53 27.2 5.6 7.0 (53) 4.3 
PatientPhenotype of LDMutationSexAge (years)BMI (kg/m2)Leptin (μg/L)HbA1c
(% [mmol/mol])TG (mmol/L)
Partial LMNA 23 27.4 5.3 6.4 (46) 16.3 
Partial LMNA 34 28.7 5.2 8.9 (74) 2.4 
Partial LMNA 48 27.4 9.8 6.6 (49) 2.5 
Generalized ND 16 17.4 <0.48 8.4 (68) 9.2 
Partial ND 41 30 3.6 8.0 (64) 7.9 
Generalized ND 33 20.7 <0.48 8.1 (65) 37.1 
Partial PPARγ 55 33.5 6.7 6.0 (42) 23.2 
Partial ND 39 30.8 11.2 7.6 (60) 15.6 
Partial PPARγ 53 27.2 5.6 7.0 (53) 4.3 

LMNA, lamin A/C; ND, not detected; PPARγ, peroxisome proliferator–activated receptor-γ. F, female; M, male.

Medication

The leptin analog metreleptin was used for treatment. Metreleptin was provided by Amylin (San Diego, CA), Bristol-Myers Squibb (Munich, Germany), AstraZeneca (London, U.K.), and Aegerion Pharmaceuticals (Cambridge, MA) and applied subcutaneously. Dosing was recommended by the respective manufacturer to achieve physiological replacement. Patients 1–3 (all female) were administered metreleptin 0.04 mg/kg body weight/day b.i.d. for the first week and 0.08 mg/kg body weight/day thereafter, resulting in doses between 2.9 and 7.8 mg/day. For patients 4–9, dosing changed due to modified instructions by the manufacturer. Metreleptin was administered once daily at 2.5 mg/day for men and 5 mg/day for women, independent of body weight.

Experimental Design

Experiments were performed between 2010 and 2014. Behavioral tests and MRI scanning were performed at six time points: 1 day before start of metreleptin supplementation and after 1, 4, 12, 26, and 52 weeks of metreleptin treatment. On each measurement day, the same set of questionnaires and behavioral tests was completed as described in the next section. All patients were asked to have a small lunch at 12:00 p.m. and to fast thereafter until 5:00 p.m. Then, a standard meal consisting of 20% of the daily energy requirements calculated for each patient was consumed. Because leptin physiologically mediates satiety, differences between leptin deficiency and imitated physiological leptin levels due to metreleptin treatment were expected to be most pronounced in the sated state and, therefore, the mentioned calorie amount was chosen to create a state of moderate satiety. We did not choose a higher percentage of daily energy requirements to avoid both a ceiling effect in extreme fullness and postprandial tiredness during the following fMRI scan. Before and after the meal, patients filled in visual analog scales (VASs). At 6:00 p.m., the MRI scan was performed. The next morning at 8:00 a.m., a fasting blood sample was taken for assessment of metabolic parameters, including fasting TG, HbA1c, and serum leptin concentrations.

Questionnaires and Behavioral Tests

Before all other measurements, the German versions of the Three Factor Eating Questionnaire (TFEQ) (17) (or Fragebogen zum Essverhalten [18]) and Inventory of Eating Behavior and Weight Problems (Inventar zum Essverhalten und Gewichtsproblemen [IEG]) (19) were completed. Because the TFEQ and IEG refer more to long-term than to short-term attitudes and feelings, neither test was performed 1 week after initiation of metreleptin treatment. A complete list of the 14 scales of the IEG with German titles and English translations is shown as Supplementary Table 1. The VAS were bars of 100 mm in length for the assessment of hunger and satiety feelings, where 0 mm indicated no hunger or satiety and 100 mm indicated extreme hunger or satiety. The picture rating task was performed in a designated room with as little distraction as possible. On a computer screen, 200 food and 50 nonfood pictures were presented in random order and rated through a keypad (four keys) for valence (food pictures: “How tasty do you find the depicted food item?” [1 = not at all tasty; 4 = extremely tasty]; nonfood pictures: “How much do you like the depicted object?” [1 = not at all; 4 = very much]).

fMRI Paradigm, Technical Parameters, and Data Processing

The fMRI scan was performed in resting state. Patients inside the scanner were in a supine position and looking at a black screen with a white fixation cross. A whole-body 3-T MAGNETOM Trio, A Tim System, scanner (Siemens, Erlangen, Germany) with a 32-channel head coil was used. In each scanning session, resting state fMRI data were acquired by using a gradient echo, echo planar imaging sequence. The following parameters were used: 300 whole-brain volumes, 64 × 64 acquisition matrix, and slice thickness of 4 mm (1-mm gap), resulting in a nominal voxel size of 3 × 3 × 5 mm3. Further imaging parameters were 30 axial slices, repetition time of 2,300 ms, echo time of 30 ms, flip angle of 90°, and bandwidth of 1,817 Hz/pixel.

Preprocessing of the fMRI data was performed by using Statistical Parametric Mapping (SPM) 8 software, including estimation and correction for motion and echo planar imaging deformation. The normalization was performed by registering the individual three-dimensional high-resolution T1-weighted structural image onto the functional images. This individual anatomical image was further processed by the unified segmentation algorithm (20), and the resulting deformation field was applied onto the functional images. After normalization, the resulting voxel size of the functional images was interpolated to an isotropic voxel size of 3 × 3 × 3 mm3. In the final step of the preprocessing, the functional images were smoothed by using a Gaussian smoothing kernel of 8 mm full width at half maximum.

To identify treatment-related connectivity changes, eigenvector centrality (EC) mapping was performed using the Leipzig Image Processing and Statistical Inference Algorithms software package (21). EC provides a measure for detecting central hubs within a brain network by using an algorithm similar to the Google PageRank algorithm (22). For all voxels, a similarity matrix was generated, including Pearson correlation coefficients, among all resting state fMRI time courses. To use a similarity matrix with only positive numbers, all negative entries were set to zero before computing the EC. In a second approach, we also used the absolute value, taking all values of the similarity matrix into account when computing the EC measure. Note that according to the theorem of Peron and Frobenius (23), the similarity matrix has a unique real largest eigenvalue, and the corresponding eigenvector has strictly positive components. Then, the EC map was generated by using the components of this eigenvector to determine the EC of all voxels.

Within SPM, group-level statistical analysis of all six EC maps for all subjects used the general linear model with a flexible factorial design with factors subject and time. A weighted sum of the parameter estimates was statistically assessed by using a contrast vector generated by the a priori hypothesis of an increased EC over time. The resulting statistical parametric map was processed by using a voxelwise threshold of P < 0.005. Taking the multiple comparison problem into account, clusters were detected with a minimum size of 80 voxels to obtain clusters with a false discovery rate (FDR)–corrected P < 0.05.

Anthropometric and Metabolic Parameters in Patients With LD

Baseline characteristics of all patients are summarized in Table 1. Mean ± SEM age was 38 ± 4 years, and BMI was 27.0 ± 1.7 kg/m2. Baseline leptin was 5.3 ± 1.2 μg/L, HbA1c was 7.4 ± 0.3%, and TGs were 13.2 ± 3.8 mmol/L. Changes in BMI, HbA1c, and TGs during metreleptin treatment are summarized in Supplementary Table 2.

Valence of Food/Nonfood Pictures and Hunger/Satiety Ratings

The average rating score of food pictures was 2.76 ± 0.12 and for nonfood pictures, 2.55 ± 0.08 at baseline (Fig. 1A). Valence of food pictures decreased after initiation of metreleptin treatment, with significant decreases observed at 1 week, 4 weeks, and 52 weeks (P < 0.05) as well as trends at 12 weeks (P = 0.06) and 26 weeks (P = 0.07). In contrast, rating scores of nonfood pictures did not change significantly throughout the 52 weeks of metreleptin treatment (Fig. 1A).

Figure 1

Liking ratings of food and nonfood pictures (A) and VAS for hunger and satiety (B) before, 5 min after, and 120 min after a standardized meal. *P < 0.05, **P < 0.01 compared with baseline; †P < 0.05 compared with 26 weeks as assessed by two-tailed paired Student t test.

Figure 1

Liking ratings of food and nonfood pictures (A) and VAS for hunger and satiety (B) before, 5 min after, and 120 min after a standardized meal. *P < 0.05, **P < 0.01 compared with baseline; †P < 0.05 compared with 26 weeks as assessed by two-tailed paired Student t test.

Fasting hunger rated on VAS was 54 ± 9 mm at baseline (Fig. 1B). Hunger ratings continuously decreased over the first 26 weeks of metreleptin treatment, with the lowest scores detectable at 26 weeks (18 ± 6 mm, P = 0.002). Fasting hunger at 52 weeks was significantly higher than at 26 weeks (44 ± 9 mm, P = 0.04). Satiety rated 5 min after the meal was 72 ± 8 mm at baseline. Satiety ratings 5 min after the meal continuously increased over the first 26 weeks of metreleptin treatment, with the highest scores detectable at 26 weeks (93 ± 2 mm, P = 0.03). Satiety rated 5 min after the meal at 52 weeks (72 ± 8 mm) was significantly lower than at 26 weeks (P = 0.04) and equal to baseline levels. Satiety rated 120 min after the meal was 56 ± 9 mm at baseline and increased to 78 ± 5 mm after 1 week (P = 0.03) and 77 ± 8 mm after 4 weeks (P = 0.051). Satiety ratings 120 min after the meal at 12, 26, and 52 weeks were not significantly different from baseline, with similar ratings seen at 26 (72 ± 8 mm) and 52 (70 ± 9 mm) weeks, respectively (Fig. 1B). Ratings for tastiness of the test meal were between 63 and 70 mm on the VAS and did not change significantly throughout the 52 weeks of metreleptin treatment (data not shown).

Food Questionnaires

On the TFEQ, average baseline score for scale 2 (disinhibition) was 7.0 ± 1.0, which significantly decreased to 4.2 ± 1.1 as early as 4 weeks after initiation of metreleptin treatment (P < 0.05) (Fig. 2A). The average score remained significantly decreased compared with baseline up to 26 weeks (P < 0.05), and a strong trend was seen after 52 weeks (4.3 ± 0.8, P = 0.052). The average baseline score for scale 3 (hunger) was 8.9 ± 0.9, which also decreased to 4.4 ± 0.9 after 4 weeks of metreleptin treatment (P < 0.01). The average score further decreased, with the lowest values detectable at 26 weeks (2.7 ± 0.8, P < 0.001) and a significantly lower score detectable after 52 weeks (3.1 ± 1.1, P < 0.001). In contrast, average scores for scale 1 (cognitive restraint of eating) did not significantly change throughout the 52 weeks of metreleptin treatment (Fig. 2A).

Figure 2

All scales of the TFEQ (A) and 5 of 14 scales of the IEG (B) showing significant changes after initiation of metreleptin treatment. Values were obtained as described in 2research design and methods and Supplementary Table 1. *P < 0.05, **P < 0.01, ***P < 0.001 compared with baseline as assessed by two-tailed paired Student t test.

Figure 2

All scales of the TFEQ (A) and 5 of 14 scales of the IEG (B) showing significant changes after initiation of metreleptin treatment. Values were obtained as described in 2research design and methods and Supplementary Table 1. *P < 0.05, **P < 0.01, ***P < 0.001 compared with baseline as assessed by two-tailed paired Student t test.

On the IEG questionnaire, average scores for scale 1 (importance of eating), scale 2 (strength and triggering of desire to eat), scale 9 (attitude towards obese persons), and scale 11 (eating between meals) all significantly decreased at least at one time point after initiation of metreleptin treatment compared with baseline levels (Fig. 2B). Furthermore, the value for scale 7 (cognitive restraint of eating) was significantly higher at 52 weeks of metreleptin treatment (11.8 ± 2.1) compared with baseline (9.0 ± 1.9, P = 0.02) (Fig. 2B). In contrast, values on all other scales were not significantly affected by metreleptin treatment (data not shown). For original German wording and English translation of scale titles, refer to Supplementary Table 1.

fMRI Data

Using resting state fMRI and EC mapping (ECM), a significant increase of brain connectivity was detected over the course of metreleptin treatment. A significant EC increase over all six measurements was found in three brain regions: hypothalamus (Montreal Neurological Institute [MNI] coordinates x, y, z [in mm]: maxima 15, 23, −8, T = 4.22; 3, 5, −11, T = 4.20; and −6, 11, −11, T = 3.24; P on cluster level = 0.040, FDR corrected), insula/superior temporal gyrus (STG) (MNI coordinates local maximum 51, −13, 7; T = 4.48; P on cluster level = 0.004, FDR corrected), and medial prefrontal cortex (mPFC) (MNI coordinates local maximum −6, 56, 16; T = 4.82; P on cluster level < 0.001, FDR corrected) (Fig. 3). To further ascertain that the significant EC increases found in the midbrain cluster map the hypothalamus, a conjunction between whole-brain ECM analysis and a hypothalamus mask created with Wake Forest University PickAtlas software (24) was performed. Here, voxels within the mask of hypothalamus showed an increase of EC over time (Supplementary Fig. 1). The maximum of the cluster was located in 6, 2, and –17, and both peak and cluster were significant (P < 0.05, family-wise error corrected) (Supplementary Fig. 1).

Figure 3

Parametric contrast with increase of EC over time with six measurements (–2.5, –1.5, –0.5, 0.5, 1.5, 2.5) over 52 weeks of metreleptin treatment (yellow/orange). EC values were obtained using repeated sessions of resting state fMRI before metreleptin therapy as well as after 1, 4, 12, 26, and 52 weeks of treatment. Local maxima are given in millimeters for MNI coordinates x, y, and z. In addition, mean ± SEM–fitted EC values at local maxima are presented for every measurement. corr, corrected.

Figure 3

Parametric contrast with increase of EC over time with six measurements (–2.5, –1.5, –0.5, 0.5, 1.5, 2.5) over 52 weeks of metreleptin treatment (yellow/orange). EC values were obtained using repeated sessions of resting state fMRI before metreleptin therapy as well as after 1, 4, 12, 26, and 52 weeks of treatment. Local maxima are given in millimeters for MNI coordinates x, y, and z. In addition, mean ± SEM–fitted EC values at local maxima are presented for every measurement. corr, corrected.

Of note, a significant EC increase in all three brain regions was detected with both approaches of dealing with negative values in the correlation matrix (i.e., setting all negative values to zero, using the absolute value). When the two male subjects were excluded from the analysis, the results remained similar (Supplementary Fig. 2). Furthermore, the same brain regions were also seen in all subjects (n = 9) when contrasting baseline (V1) against 52 weeks of metreleptin treatment (V6) (data not shown). In contrast with the linear increase over time (−2.5, –1.5, –0.5, 0.5, 1.5, 2.5), metreleptin treatment over 1 year also increased connectivity with other EC measures as calculated with the fast ECM SPM toolbox (25), that is, in the hypothalamus as assessed by norm ECM and degree ECM as well as in the insula/STG and mPFC as assessed by norm ECM and rank ECM (Supplementary Fig. 3).

In connectivity analysis with region-wise pairs using the Automated Anatomical Labeling atlas (26), connectivity for the insula/STG was also increased over the course of metreleptin treatment (Supplementary Fig. 4). The hypothalamus and the mPFC are not defined by the Automated Anatomical Labeling atlas. By using the inverse contrast of decreased EC over time, we obtained a region in the vicinity of the precuneus, a part of the so-called default mode network of the human brain (Supplementary Fig. 5).

For the first time in our knowledge, this study demonstrated that metreleptin treatment in patients with LD over 52 weeks is associated with significantly increased resting state connectivity in the hypothalamus, insula/STG, and mPFC (i.e., in both homeostatic and hedonic brain areas). These observed effects are accompanied by significant decreases in self-reported pre- and postprandial hunger feelings as rated with a VAS (a measure for homeostatic hunger) and food liking ratings in the fed state (a measure for the hedonic perception of food).

First, we observed a connectivity increase in the hypothalamus, the homeostatic center of the brain, over the 52 weeks of metreleptin treatment. Behavioral data showed reduced hunger ratings in the fasted state and increased satiety ratings after a standard meal during the first 26 weeks of metreleptin treatment. These findings are in accordance with independent studies on metreleptin treatment in patients with LD (4,13). Furthermore, TFEQ responses showed decreased scores for scale 3 (hunger) after initiation of metreleptin. Lower scores indicate that hunger feelings (which are often perceived as disturbing) are decreased (18). Of note in this context is that another physiological anorexigenic peptide hormone, the GLP-1 agonist exenatide, had similar effects on the hypothalamus in fMRI connectivity analysis as well as on VAS-assessed hunger and satiety in obese subjects in another study from our group (27). These results combined support the hypothesis that leptin substitution improves homeostatic satiety signaling through the hypothalamus. However, causality cannot be established with the current design, and further investigations are required.

Second, connectivity increased in the insula/STG during the 52 weeks of metreleptin treatment. The insula is the gustatory cortex of the brain and is involved in interoception (i.e., internal sensing of food qualities like odor, taste, and nutrient composition) (28). Furthermore, it is supposed to map the ongoing physiological state of the body through thalamocortical pathways (29). Moreover, the insula is an important region in reward processes believed to play a role in the valuation of reward, and alterations are found in diseases with disrupted reward and valuation-like addictive behavior (29). In the leptin-deficient state, the current study patients anecdotally described an addiction-like affinity with food, with large parts of their free time revolving around food preparation and consumption. After a meal, satiety only persisted for ∼1 h. After metreleptin treatment, patients initially experienced longer periods of satiety after a meal, reduced meal frequencies, and lost interest in thoughts about food. These descriptions are underlined by significant decreases of IEG scores for scale 1 (importance of eating), scale 2 (strength and triggering of desire to eat), and scale 11 (eating between meals). Furthermore, the behavioral data indicate a stronger self-control of eating behavior after initiation of leptin substitution, as shown by IEG scores for scale 7 (cognitive restraint on eating), which were significantly increased during metreleptin treatment. The score of the identically named scale 1 of the TFEQ also increased but did not reach the level of statistical significance. Unfortunately, we did not assess cognitive abilities linked to the STG (30) because the behavioral focus of the current study was primarily on eating regulation. Overall, the findings agree with the hypothesis that metreleptin improves physiological interoception of food through an increase of connectivity of the insula/STG compared with a leptin-deficient state. Future studies need to further investigate this hypothesis.

Third, metreleptin treatment was also associated with increased connectivity in the mPFC, which is a brain region involved in the assignment of incentive (i.e., motivational) value to food stimuli together with the orbitofrontal cortex and, thus, drives feeding behavior (31,32). In accordance with these imaging findings, we found a decrease of liking ratings of food pictures with metreleptin therapy. TFEQ values for scale 2 (disinhibition), which indicates how vulnerable a person’s eating behavior is through external (e.g., smell and sight of food) and internal (e.g., emotions) distractors, decreased. These data are supported by findings of an independent study with an event-related fMRI paradigm that investigated acute brain activity changes during presentation of food pictures in two adolescents with congenital leptin deficiency (33). The authors demonstrated that positive correlations of brain activations in the nucleus accumbens and caudate nucleus (important regions of the dopaminergic reward system) observed in leptin deficiency were not seen any more in the metreleptin-treated state, suggesting that leptin is necessary to suppress the incentive motivational value to food stimuli in the fed state.

We did not find a significant correlation between changes of the metabolic parameters HbA1c, TGs, and total, HDL, and LDL cholesterol and brain imaging results (data not shown). These findings do not support the hypothesis that the metabolic changes seen with metreleptin significantly affect the central nervous findings. However, we cannot exclude the possibility that our methods were not sensitive enough or that the sample size was too small.

Strengths of this study include being the first fMRI study in treatment-naive patients with LD to examine the effects of metreleptin on brain connectivity and analyze five time points after initiation of treatment ranging from 1 to 52 weeks. Furthermore, with a wide range of neuropsychological assessments, we were able to differentially picture the effects of metreleptin treatment on the various facets of hunger regulation and eating behavior. However, several limitations must be discussed. First, the study lacked a placebo or healthy control group; therefore, the experimental design did not allow the distinction between metreleptin treatment effects and nonspecific order effects. Second, measurements may well have changed across repeated assessments for a variety of reasons (e.g., habituation). Third, phase of the menstrual cycle also affects eating behaviors and might have influenced the findings. However, in only two of the nine patients, intraindividual variation in sex hormone levels can be suspected among the six measurements. Fourth, metabolic improvements in patients with LD on metreleptin therapy have already been demonstrated in the past in larger samples (2); thus, the current study sample size of nine patients is small for an fMRI study, especially when taking into account that resting state fMRI connectivity involves numerous statistical operations on the three-dimensional volume space. However, no study with n > 1 has been published so far in metreleptin treatment–naive subjects with leptin-deficiency. Furthermore, the current study is the first to describe metreleptin treatment–associated alterations in resting state connectivity compared with published fMRI studies with event-related designs ranging from n = 1 to 3 subjects (3336); one study reported on 10 subjects who were not treatment naive (13). A replication of the current fMRI results in larger samples would be valuable.

Taken together, we have elucidated the long-term effects of metreleptin on brain connectivity in patients with LD. Leptin substitution causes long-term changes of hedonic and homeostatic central nervous networks that regulate eating behavior and that are accompanied by decreased hunger feelings and a diminished incentive value of food. Future studies need to assess whether metreleptin treatment in LD restores physiological processes important for the development of satiety through these mechanisms.

Funding. This work was supported by the German Research Foundation (Deutsche Forschungsgemeinschaft [DFG]) CRC 1052 “Obesity Mechanisms” projects A05 to A.H., A01 to A.V. and M.S., A06 to B.P., and C06 to M.F.; the Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung [BMBF]), Germany, IFB AdiposityDiseases grant no. 01EO1501 projects K7-83 and K7-84 to A.H. and project K6a-87 to M.F.; and the Deutsches Zentrum für Diabetesforschung (DZD) grant no. 82DZD00601.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. H.S. contributed to the study concept and design, performance of experiments, data analysis, and writing and editing of the manuscript. K.Mü. contributed to the study concept and design, data analysis, and editing of the manuscript. A.H. contributed to the study concept and design, performance of experiments, data analysis, and editing of the manuscript. K.Mi. contributed to the writing and editing of the manuscript. J.P. contributed to the performance of experiments, data analysis, and editing of the manuscript. A.V. and M.S. contributed to the study concept and design and editing of the manuscript. B.P. contributed to the study concept and design, data analysis, and writing and editing of the manuscript. M.F. contributed to the study concept and design and writing and editing of the manuscript. H.S. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation. Parts of this study were presented at the 73rd Scientific Sessions of the American Diabetes Association, Chicago, IL, 21–25 June 2013.

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Supplementary data