Unexpected identification of obesity-associated mutations in LEP and MC4R genes in patients with anorexia nervosa

Unexpected identification of obesity-associated mutations in LEP and MC4R genes in patients with anorexia nervosa | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Unexpected identification of obesity-associated mutations in LEP and MC4R genes in patients with anorexia nervosa Luisa Sophie Rajcsanyi, Yiran Zheng, Beate Herpertz-Dahlmann, and 13 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3850003/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Mar, 2024 Read the published version in Scientific Reports → Version 1 posted 9 You are reading this latest preprint version Abstract Mutations leading to a reduced or loss of function in genes of the leptin-melanocortin system confer a risk for monogenic forms of obesity. Yet, gain of function variants in the melanocortin-4-receptor ( MC4R ) gene predispose to a lower BMI. In individuals with reduced body weight, we thus expected mutations leading to an enhanced function in the respective genes, like leptin ( LEP) and MC4R . Therefore, we have Sanger sequenced the coding regions of LEP and MC4R in 462 female patients with AN, and 445 healthy-lean controls. In total, we have observed four and eight variants in LEP and MC4R , respectively. Previous studies showed different functional in vitro effects for the detected frameshift and non-synonymous variants: ( 1 ) LEP : reduced/loss of function (p.Val94Met), ( 2 ) MC4R : gain of function (p.Val103Ile, p.Ile251Leu), reduced or loss of function (p.Thr112Met, p.Ser127Leu, p.Leu211 fs X) and without functional in vitro data (p.Val50Leut). In LEP , the variant p.Val94Met was detected in one patient with AN. For MC4R variants, one patient with AN carried the frameshift variant p.Leu211 fs X. One patient with AN was heterozygous for two variants at the MC4R (p.Val103Ile and p.Ser127Leu). All other functionally relevant variants were detected in similar frequencies in patients with AN and lean individuals. Biological sciences/Genetics/Genotype Biological sciences/Genetics/Medical genetics Biological sciences/Genetics/Mutation Biological sciences/Genetics/Sequencing Introduction Anorexia nervosa (AN) is marked by a diminished body weight, a pronounced fear of gaining weight and a distorted body image 1 . Among psychiatric disorders, AN exhibits the highest mortality rates 2–7 . Formal genetic studies revealed a robust genetic component for AN. In fact, twin-based studies have estimated a heritability for AN between 28 and 74%, depending on stringency of its definition and sample size 8 . In the last decade, genome-wide association studies (GWAS) uncovered eight genetic loci associated with AN 9 . Energy homeostasis and consequently, body weight regulation, are modulated by the leptin-melanocortin-system exerting its functions in the hypothalamus. Leptin (LEP) is secreted by the adipose tissue (AT) and relays adaptive signals about the mass of the AT and the nutritional status to the brain. In the hypothalamic arcuate nucleus, leptin binds to the leptin receptor leading to the inhibition of the orexigenic agouti-related peptide (AgRP)/neuropeptide Y (NPY) neurons, while stimulating the anorexigenic pro-opiomelanocortin (POMC)/cocaine and amphetamine regulated transcript (CART) neurons. The released POMC is post-transcriptionally processed into α-melanocyte-stimulating hormone (α-MSH), which subsequently bind to the melanocortin-4-receptor (MC4R). The resultant activation of MC4R leads to the production of satiety signals and consequently to a lower food intake and higher energy expenditure 10–12,13 . Disruption of this regulation by loss of function (LoF) variants is known to be associated with severe monogenic forms of obesity 13,14 . The variants include non-synonymous and nonsense LEP variants 15–20 . Yet, gain of function (GoF) variants, e.g. in MC4R 21–23 , predispose to a lower body mass index (BMI). Further, previous studies have reported shared genetic loci for reduced BMI and AN risk 24–26 . Generally, patients with acute AN have considerably reduced serum leptin levels compared to BMI-matched controls. An increase in weight is accompanied by an increase in leptin 27–29,30 . Besides, a Mendelian randomization study concluded that low leptin levels are correlated with a higher risk of AN 31 . Treating patients with AN off-label with recombinant leptin improved cognition, behaviour and mood 32–34 . Despite emerging evidence for the crucial role of the leptin-melanocortin system in the aetiology of AN 31,35 , no associations of variants in LEP in patients with AN have been described so far 9,36,37 . In MC4R , the mutant allele of the variant rs2229616 was previously shown to have a BMI-decreasing effect 21,38 . Previously, we have screened both genes in rather small study groups of patients with AN 36,39 . In the present study, we expanded our previous findings by Sanger sequencing of the coding regions of LEP and MC4R in larger study groups comprising 462 acutely ill or recovered women with AN and 445 healthy-lean controls. Based on in silico analyses and previously published in vitro and in vivo data, we subsequently assessed the functional consequences of the detected variants. Results Variants in the coding regions of LEP The sequencing of the coding region of LEP revealed a total of four rare (minor allele frequency (MAF) ≤ 0.01%) variants (see Table 2 ). All identified carriers are heterozygous for the respective variant. Table 1 Phenotypic characteristics of the investigated study groups. Sample Status n % female Age in years BMI in kg/m² BMI-SDS LMS Patients with AN Total cases 462 100 20.83 (8.63) 16.48 (2.77) -2.55 (1.58) Acutely ill 368 100 19.31 (7.70) 15.43 (1.67) -2.99 (1.40) Recovered 94 100 26.76 (9.42) 20.57 (2.40) -0.82 (0.90) Healthy-lean individuals Controls 445 61.7 26.04 (5.77) 18.08 (1.13) -2.77 (0.58) All data is represented as mean (SD). BMI: body mass index. BMI-SDS LMS : body mass index standard deviation score. SD: standard deviation Table 2 Minor allele frequencies of the detected variants in LEP and MC4R . Gene Variant Reference allele Minor allele Amino acid exchange Patients with AN Healthy-lean individuals European females in gnomAD 11 12 22 MAF 11 12 22 MAF MAF LEP rs201523305 C T Cys7= 461 1 0 0.001 445 0 0 0 0.0002 rs13306517 A G Gln25= 462 0 0 0 444 1 0 0.001 0.0009 No rsID g.128254532 C T Ser91= 461 1 0 0.001 445 0 0 0 NA rs17151919 G A Val94Met 461 1 0 0.001 445 0 0 0 0.0005 MC4R rs121913557 C A Val50Leu 461 1 0 0.001 444 1 0 0.001 0 rs2229616 C T Val103Ile 447 15 0 0.02 432 13 0 0.015 0.02 rs13447329 G A Thr112Met 461 1 0 0.001 443 2 0 0.002 0.002 rs13447331 G A Ser127Leu 461 1 0 0.001 445 0 0 0 0.0002 Novel variant g.60371891 A G Tyr153= 461 1 0 0.001 445 0 0 0 NA No rsID g.60371771 G A Val193= 462 0 0 0 444 1 0 0.001 NA rs13447338 GAGA - Leu211fsX 461 1 0 0.001 445 0 0 0 0.00002 rs52820871 T G Ile251Leu 456 6 0 0.006 437 8 0 0.009 0.01 Here, all detected variants in the coding regions of LEP and MC4R are represented for the respective study groups. The alleles are assigned based on the forward strand. Additionally, the minor allele frequency of the non-Finnish European females in the Genome Aggregation Database (gnomAD) for each SNP is given. Some genetic variants are not represented in the used version (v2.1.1) of gnomAD ( NA ). 11: homozygous wildtype. 12: heterozygous. 22: homozygous minor allele. gnomAD: Genome Aggregation Database. MAF: minor allele frequency. NA : not available. One variant led to a non-conservative amino acid exchange (rs17151919, p.Val94Met), while all others were synonymous variants (rs201523305, p.Cys7=; rs13306517, p.Gln25 = and a variant without an rsID, p.Ser91=). The non-synonymous variant (rs17151919) was detected in the heterozygous state in an acutely ill female patient with AN (age: 34.12 years old; BMI: 15.94 kg/m²; BMI-SDS LMS : -3.62). In silico tools, like MutationTaster2021 40 and PredictSNP2 41 , hinted at an overall non-pathogenic effect. Yet, the resultant amino acid substitution was predicted to have a destabilizing impact on LEP (see Table 3 ). The mutant allele (Met94; in mature protein this equals position 73; see Supplementary Fig. 1) was already reported to be associated with lower leptin levels and a higher childhood BMI in individuals of African ancestry 42 . At baseline, each mutant allele added approximately 2.6 kg to the carrier’s weight, while the weight increased to 4.8 kg at year 20 43 . No associations were detected in Europeans, as this variant was extremely rare in this population 42 . Functional in vitro analyses reported a decreased leptin secretion in human embryonic kidney 293 cells caused by the substitution of valine by methionine 42 . Table 3 In silico analyses for the detected variants in LEP and MC4R Gene Variant Amino acid exchange Predictions for all variants Predictions for non-synonymous variants ESEfinder Mutation Taster2021 PredictSNP2 PANTHER-PSEP CUPSAT SIFT Splice site Prediction Prediction Prediction Stability Torsion Prediction LEP rs201523305 Cys7= Changed Benign Neutral - - - - rs13306517 Gln25= Not changed Benign Neutral - - - - No rsID g.128254532C/T Ser91= Not changed Benign Neutral - - - - rs17151919 Val94Met Not changed Benign Neutral Probably benign Destabilizing Favourable Tolerated MC4R rs121913557 Val50Leu Changed Deleterious Deleterious Probably benign Destabilizing Favourable Deleterious rs2229616 Val103Ile Changed Benign Deleterious Probably benign Destabilizing Favourable Tolerated rs13447329 Thr112Met Changed Benign Neutral Probably benign - - Tolerated rs13447331 Ser127Leu Changed Deleterious Deleterious Probably damaging Stabilizing Favourable Tolerated Novel variant g.60371891A/G Tyr153= Changed Benign Neutral - - - - No rsID g.60371771G/A Val193= Not changed Benign Neutral - - - - rs13447338 Leu211fsX Changed - - - - - - rs52820871 Ile251Leu Changed Benign Neutral Probably benign Destabilizing Favourable Tolerated To predict putative effects of the mutant alleles, various in silico tools were applied. Putative impacts on splicing products were examined with the tool ESEfinder ( 75 ). The general pathogenicity was predicted with MutationTaster2021 ( 40 ) and PredictSNP2 ( 41 ). The latter being a consensus classifier condensing results of multiple tools, like CADD and FATHMM. Indications for impacts on the proteins were investigated with PANTHER-PSEP ( 76 ), CUPSAT ( 77 ) and SIFT ( 78 ). Tools predicting effects on the protein were only applicable for non-synonymous variants. Yet, as the used protein reference sequence of MC4R was incomplete, the non-synonymous variant rs13447329 (p.Thr112Met) could not be analysed with CUPSAT and SIFT. Moreover, three synonymous variants rs201523305 (p.Cys7=), rs13306517 (p.Gln25=) and a variant without an assigned rsID (p.Ser91=) were determined (see Table 2 ). The latter variant (p.Ser91=) had already been detected in our previous mutation screen 36 . One recovered patient with AN (BMI: 21.23 kg/m²; BMI-SDS LMS : -1.11) harboured the variant rs201523305 (p.Cys7=) predicted to alter splice sites (see Table 3 ). The variant leading to p.Ser91 = was found in one acutely ill adolescent with AN (BMI: 15.43 kg/m²; BMI-SDS LMS : − 3.03). Again, in silico tools hinted at a benign impact (see Table 3 ). The variant rs13306517 (p.Gln25=) was exclusively detected in one lean control individual (see Table 2 ). This variant was implied not to have functional implications (see Table 3 ). Beyond, no functional studies have previously been published for these variants (see Supplementary Tables 2 and 4). Variants in the coding region of MC4R Eight variants located in the coding sequence of MC4R were identified (see Table 2 ). Five of those are non-synonymous variants (rs121913557, p.Val50Leu; rs2229616, p.Val103Ile; rs13447329, p.Thr112Met; rs13447331, p.Ser127Leu; rs52820871, p.Ile251Leu; for structural positions of non-synonymous variants see Supplementary Fig. 2). Additionally, one frameshift (rs13447338, p.Leu211 fs X), one novel synonymous (p.Tyr153=) and one synonymous variant without an assigned rsID (p.Val193=) were determined (see Table 2 ). We observed the non-synonymous variants rs2229616 (p.Val103Ile) and rs52820871 (p.Ile251Leu) in similar frequencies in our 462 patients with AN, and 445 healthy-lean controls (see Table 2 ). Our in silico analyses hinted at a putative deleterious effect caused by rs2229616 without affecting splice sites and the protein’s torsion, while rs52828071 was predicted to be overall benign but has the potential to destabilize MC4R (see Table 3 ). Numerous studies have already reported a reduced risk for obesity and an association with a lower BMI of the infrequent alleles of rs2229616 and rs52820871 22,21,44 . In 2004, Geller and colleagues detected a reduced transmission rate of the Ile103 allele in an analysis of family-based samples, thus providing initial evidence for an obesity-protective effect of this variant 21 . Functional implications of both frequent variants have been thoroughly studied, as well. For instance, the introduction of the variants in inbred mice, showed no significant difference in food intake and BMI between homozygous or heterozygous mice for each mutant and their wildtype (WT) littermates. Yet, homozygous female mice ( MC4R V103I/V103I and MC4R I251L/I251L ) had a reduced longitudinal length and their white adipose tissue weighed less in relation to their WT littermates. Albeit, when fed a high-fat diet, these mice’s adiposity resembled those of their littermates not carrying a variant 23 . Another study showed that variants p.Val103Ile and p.Ile251Leu can be characterised as GoF variants as they have a significant bias towards the ß-arrestin recruitment rather than cyclic adenosine monophosphate (cAMP)-mediated signalling. Beyond, it was determined that the MC4R carrying the mutant Ile103 allele did not internalize like the WT MC4R and consequently exhibited a stable expression on the cell surface upon agonist stimulation 22 . In accordance, another study supported a deviating signalling behaviour due to p.Val103Ile yielding in GoF characteristics 45 . Conflicting to these findings, others reported that both variants displayed an elevated presence at the plasma membrane. Upon agonist stimulation, solely p.Ile251Leu led to a reduced internalisation, while the MC4R with the mutant Ile103 allele maintained an unaltered internalisation 46 . Besides, multiple studies did not ascertain any functional differences between the WT and mutant MC4R for p.Val103Ile and p.Ile251Leu 21,47–50 . We further have detected one lean control individual (BMI: 17.00 kg/m²; BMI-SDS: -2.64) harbouring two frequent variants leading to p.Val103Ile and p.Ile251Leu. Similarly, one patient with AN carried the common rs2229616 (p.Val103Ile) and the rare variant rs13447331 (p.Ser127Leu). This patient had a restrictive AN. At admission the patient had a weight of 45.3 kg being 169.5 cm tall (BMI: 15.67 kg/m²; 4th BMI-percentile). During the 19 weeks in-patient treatment 6 kg were gained resulting in a BMI of 17.75 kg/m² at discharge. Leptin levels were 1.66 µg/l at admission and increased during treatment up to 5.59 µg/l at discharge. After 2.5 years, the patient had a BMI of 22.66 kg/m² (weight: 66 kg), while leptin levels were 43.31 µg/l. In vitro studies on double mutant receptors with p.Val103Ile and p.Ser127Leu demonstrated that these can cause a reduced efficacy and potency 51 and are less abundant on cell surfaces 52 . An increase in the cAMP accumulation in relation to the single mutant MC4R carrying the Leu127 allele was determined 52 . We did not detect the rare variant leading to the non-conservative amino acid substitution from serine to leucine at position 127 in any additional individuals here (see Table 2 ). In silico tools detected functional implications for this variant, as it was rated as deleterious by MutationTaster2021 and PredictSNP2. Yet, no destabilizing potential on the MC4R protein was indicated (see Table 3 ). The frameshift mutation in MC4R (rs13447338) resulting in a truncated protein (p.Leu211fsX) was detected once in a female adolescent with AN, and not in the lean individuals (see Table 2 ). The female patient with AN displayed the restrictive form of AN. At admission, she weighed 35.10 kg while being 161 cm tall (BMI: 13.54 kg/m²; 0th BMI-percentile). During her 20-week in-patient treatment, she gained 13 kg. At discharge, she had a weight of 48.1 kg and a BMI of 18.56 kg/m². Leptin levels were 0.85 µg/l at admission and increased to 10.6 µg/l at discharge. After 2.5 years, the patient’s weight was 49 kg yielding in a BMI of 18.29 kg/m², while leptin levels were 6.61 µg/l. One in vitro study validated the functional impact of the truncated protein reporting that this variant caused a complete loss-of-function 47 . The other two non-synonymous and rare variants rs121913557 (p.Val50Leu) and rs13447329 (p.Thr112Met) were detected in both study groups. While in silico analyses hinted at a putative pathogenic and protein destabilizing impact of rs121913557, no functional implications for rs13447329 were detected (see Table 3 ). Previous studies analysing rs13447329 effects in vitro resulted in ambiguous findings. Thus, increased agonist potency and affinity for α-MSH was detected 53,54 . The mutant receptor further showed a decrease in cell surface expression in comparison to the WT 53 . Yet, multiple studies reported no functional difference of the mutant MC4R caused by this variant and the WT receptor 48,51,55 . No functional studies have been performed for the Leut50 allele of rs121913557 so far (see Supplementary Tables 3, 4 and 5). Both synonymous variants identified (p.Tyr153 = and p.Val193=) were detected each in one proband (see Table 2 ). The variant p.Val193 = was detected once in the lean control group and was implied to be benign (see Table 3 ). The other synonymous and novel variant p.Tyr153 = was found in one patient with AN (BMI: 17.29 kg/m²). For this variant, in silico tools revealed a high capacity to affect splicing and to be pathogenic (see Table 3 ). Functional in vitro studies were not available (see Supplementary Tables 3, 4 and 5). Discussion Genetic variants in genes of the leptin-melanocortin system, like LEP and MC4R , are predominantly associated with monogenic forms of obesity 13,15,18,20,36,39,56–58 . Reports emerged indicating that some variants in these genes also predispose to a lower BMI 21,22,59 . Genetic correlations between BMI, obesity and AN have been uncovered 9,24–26 . In fact, genetic variants for AN are negatively correlated with BMI, leptin levels, body fat percentage, waist circumference, overweight as well as obesity 9,26 . Previously, we have identified nine SNPs at three independent genetic loci being associated with low BMI and AN 24 . To expand the findings of our previous mutation screens 36,39 , we have sequenced the coding regions of LEP and MC4R in 462 female patients with AN, and 445 healthy-lean controls. Collectively, we have detected four variants in the LEP gene and eight variants in MC4R . Strikingly, we detected known variants leading to reduced or even loss-of-function which are associated with obesity 60,39 . Yet, the MC4R -located variants rs2229616 (p.Val103Ile) and rs52820871 (p.Ile251Leu) detected in multiple patients with AN and healthy-lean controls were already known to be associated with a lower BMI and a reduced risk for obesity 21,22,44,61 . In silico analyses indicated largely benign effects, while certain variants in both genes might impact the stability or torsion of the respective protein. The relevance of the leptin-melanocortin system in body weight regulation, energy expenditure as well as AN is already known 10,29 . Patients with AN have reduced serum leptin levels, which typically rise as weight is restored 28,29 . Strikingly, low leptin levels were linked to AN hallmark characteristics, like hyperactivity and amenorrhea 62 . A recent Mendelian randomization study has reported that low leptin levels are correlated with a higher risk of AN. This correlation was also evident when analysing an exclusive female dataset. Notably, a correlation of AN with leptin levels was not detected 31,33,34 . Beyond, off-label treatment of patients with AN (case studies) with recombinant leptin helped to improve cognition, emotions, and behavioural traits, like hyperactivity and repetitive thoughts of food 32–34 . Evidence for the involvement of leptin’s downstream target MC4R in AN is mostly based on animal models. In fact, the activation of MC4R in rats decreased food intake, while coincidently activating the hypothalamic-pituitary-adrenal axis. This activation eventually led to increased motor activity. It was suggested that genetic variants might trigger this coherence and thus lead to a prolonged stimulation of the leptin-melanocortin-system supporting the development of AN 5 . Thus, it is feasible that genetic variants in genes of the leptin-melanocortin system, especially as overlaps between genetic loci relevant for low BMI and AN are known 24,25 , impact the etiology of AN. However, to date, no significant associations of genetic variants in these genes with AN were reported 36,37 . Due to our still limited sample size and generally low allele frequencies of the here detected variants, we were also unable to report associations with AN. Nevertheless, this study was able to expand our previously published mutation screens for both genes 36,39 . Our extended sample size enabled us to discover new variants in LEP and MC4R , which potentially are relevant for AN. This emphasises the ongoing necessity for comprehensive large-scale genetic studies. Here, we did detect variants in LEP and MC4R , which were previously described to cause a partial or even complete loss of function in humans when present in a homozygous state and were thus associated with severe forms of obesity 39,51,60 . For instance, in 1999, we have described the frameshift mutation (rs13447338) yielding in a truncated MC4R in one adolescent and her mother with severe obesity 39 . In the present study, we have detected the same frameshift variant in the heterozygous state in one patient with AN. Yet, as no premorbid weight data was available, it is feasible that this patient had premorbid obesity triggering the development of AN. Further, we have to note that pathogenic variants typically are present homozygously 15,63 . For heterozygous MC4R variants, carrier develop obesity later in childhood 13 , while for heterozygous LEP variants, carriers are mainly unaffected 15,63 . As we have exclusively detected heterozygous variants in both genes, the relevance remains unknown. Yet, one patient with AN was detected to harbour two variants simultaneously (rs2229616, p.Val103Ile and rs13447331, p.Ser127Leu). Leptin levels at admission were in the expected range 64 and increased during in-patient treatment. Yet, after 2.5 years, leptin levels were rather high (43.31 µg/l). The variant leading to p.Val103Ile is known to lead to an elevated function 21,22,46 , while the amino acid substitution of serine to leucine at the 127th position was described to lead to a LoF in the majority of parameters analysed 45,55,65 (see Supplementary Tables 3, 4 and 5). Notably, certain studies also indicated no functional deviations for mutant receptors with either Ile103 or Leu127 48,49,54 . Yet, functional studies for a double mutant MC4R showed for example a reduced efficacy and potency 51 . Previously, we have also detected weight reducing variants in MC4R in patients with bulimia nervosa 66 . Further, the FTO variant rs9939609 associated with obesity 67,68 was previously identified in patients with eating disorders 69,70 . Besides a nominal association with bulimia nervosa and anorexia nervosa 69 , a synergic effect of this variant on leptin levels with an another variant in ABCA1 was described 70 . In addition, a number of studies demonstrated that two types of MC4R variants exist which can be distinguished according to their distinct signalling behaviour 22,46 . For example, variants such as the rs13447329 (p.Thr112Met) detected here, are characterised by a LoF. Other variants, such as rs2229616 (p.Val103Ile), show a GoF phenotype 22,46 . The latter GoF variants are associated with a reduced risk for obesity and a lower BMI 21,22,44 . In fact, heterozygous carriers of GoF variants weighed on overage 0.39 kg/m² less than non-carriers, while homozygotes even showed an average 0.88 kg/m² decreased BMI 22 . Similarly, an animal model with transgenic mice expressing either Val103Ile or Ile251Leu exhibited GoF phenotypes. This was even more pronounced in female than male mice. For instance, female mice carrying the variant Val103Ile homozygous had a 40% lower abdominal white adipose tissue mass than their wildtype littermates. This difference was not detected in the male transgenic mice 23 . Based on our data, we are unable to deduce a mechanism explaining how these variants may have a relevance for the phenotypes at the extremes of the weight scale. Yet, a resembling mechanism of action, as FTO ’s rs9939609 is feasible 70 . Functional in vitro studies under fasting and starvation conditions are needed to expand the findings of the general in vitro data already published for each variant. We are aware that in silico tools have their limitations and can vary substantially in their specificity 71–73 . Particularly, predicting functional implications of GoF variants was found to be more challenging by various in silico tools than finding an accurate implication for a LoF variant 74 . Hence, we have additionally checked the already published in vitro and in vivo data stated in LitVar² and on the www.mc4r.org.ukwebsite . Nevertheless, no clear-cut results were obtained for most of the variants (see Supplementary Tables 2, 3, 4 and 5). Presumably, this is due to variations in study design as well as the time period in which the studies were conducted. For example, older studies increasingly failed to detect any differences between WT and mutant MC4R. This was particularly evident for studies investigating the common GoF variant rs2229616 (p.Val103Ile) in MC4R . Supposedly, this results from the technical advances and new experimental techniques implemented in recent years. In addition, there are many variants for which no or only very few functional studies have been completed. For example, only 16 studies have been conducted on the rs17151919 variant in the leptin gene, of which just one included functional in vitro analyses (see Supplementary Table 2). Conversely, for the common variant rs2229616 in MC4R , there are over 150 studies, of which numerous also present in vitro or even in vivo data (see Supplementary Tables 3, 4 and 5). Given the reported genetic overlaps between BMI and AN 9,24–26 and GoF variants in LEP and MC4R being associated with a lower BMI and a reduced odds for obesity 21–23,59 , we have Sanger sequenced the coding regions of LEP and MC4R in 462 female patients with AN and 445 healthy-lean controls. We have detected four variants in LEP and eight variants in the coding sequence of MC4R . Here we detected variants with a partial or complete LoF in vitro in heterozygous patients with AN. Homozygous carriers of these variants typically develop obesity. Methods Study groups To detect variants in the coding regions of LEP and MC4R , 462 female patients with AN (acutely ill or recovered; age: 20.83 ± 8.63 years old; BMI: 16.48 ± 2.77 kg/m²; BMI-SDS LMS : − 2.55 ± 1.58; see Table 1 ) and 445 healthy-lean individuals without a diagnosed eating disorder (age: 26.04 ± 5.77 years old; BMI: 18.08 ± 1.13 kg/m²; BMI-SDS LMS : − 2.77 ± 0.58; see Table 1 ) were included. In previous studies we have already screened 49 patients with AN for LEP and 51 patients with AN and 25 lean individuals for MC4R 36,39 . Written informed consent was given by all participants and in case of minors by their parents. This study was approved by the Ethics committee of the respective Universities and was performed in accordance with the Declaration of Helsinki . Mutation screen The coding regions of LEP (chr7: 128,241,278–128,257,629; GRCh38; ENSG00000174697) and MC4R (chr18: 60,371,062–60,372,775; GRCh38; ENSG00000166603) were Sanger sequenced in 462 patients with AN, and 445 healthy-lean individuals (see Table 1 ) to detect genetic variants. These were identified by performing polymerase chain reactions (PCR; Veriti 96-well Thermal Cycler, Applied Biosystems, Foster City, CA, USA) with coding sequence specific primers (see Supplementary Table 1). PCR products were sent for sequencing to MicroSynth Seqlab GmbH (Göttingen, Germany). At least two independent scientists performed the sequence analysis and genotype assignment using the SeqMan Pro software (v.11.0.0, DNAstar Inc., Madison, WI, USA). Discrepancies were solved by either reaching consensus or by re-sequencing. Hardy-Weinberg-Equilibrium All detected variants were checked for compliance with the Hardy-Weinberg-Equilibrium (HWE). All variants fulfilled the HWE. In silico analyses and assessment of functional implications by published data To uncover putative functional implications of the detected variants, in silico analyses applying various tools ensued. The detected variants were analysed pertaining their potential to alter splice sites (ESEfinder 75 ) and their general pathogenicity (MutationTaster2021 40 ; PredictSNP2 41 ). Effects of non-synonymous variants on the protein structure of LEP or MC4R were examined using PANTHER-PSEP 76 , the Cologne University Protein Stability Analysis Tool 77 (CUPSAT) and the tool Sorting from Intolerant to Tolerant 78 (SIFT). The required protein structures were extracted from the Research Collaboratory for Structural Bioinformatics protein data bank (RCSB PDB): LEP (1AX8 79 ) and MC4R (7AUE 80 ). To extend the functional implications derived from the in silico analyses with previously published in vitro and in vivo data, the LitVar² 81 (accessed on Sep. 26th 2022) database was screened for each variant in LEP and MC4R detected in this study. For MC4R variants, the website www.mc4r.org.uk (accessed on Sep. 26th 2022) summarizing publications for each variant, was additionally analysed. This website is provided by the University of Cambridge Metabolic Research Laboratories. A complete list of all studies provided by LitVar² and www.mc4r.org.uk can be found in the Supplementary Table 4. Declarations Acknowledgements We thank all participants for their participation in our study. Further, we are indebted to Sieglinde Düerkop for her excellent technical support. This study was funded by the Deutsche Forschungsgemeinschaft (DFG, HI 865/2-1, DFG Research Unit FOR2488), the BMBF (01GS0820; PALGER 2017-33: 01DH19010) and the Stiftung Universitätsmedizin Essen. Author contributions BHD, JS, MdZ, Wh, SE, SZ, KG, KE, RB, MF, JH and AH recruited participants and provided the samples. LSR, YZ, PFP, JH and AH conceptualized the study. LSR and YZ performed the mutation screen and in silico analyses. LSR, YZ, JA and AH interpreted the data. LSR did the database research and wrote the manuscript. All authors read and approved the submitted version of the manuscript. Data availability statement The generated and analysed Sanger-sequencing data are available from the corresponding author on reasonable request. Data which was extracted from public websites or databases are included in the Supplementary Information files. Additional Information The author’s declare no competing interests. References Association, A. P. Diagnostic and Statistical Manual of Mental Disorders (DSM-5®) . (American Psychiatric Publishing, 2013). Arcelus, J., Mitchell, A. J., Wales, J. & Nielsen, S. Mortality rates in patients with anorexia nervosa and other eating disorders. A meta-analysis of 36 studies. Arch Gen Psychiatry 68 , 724-731, doi:10.1001/archgenpsychiatry.2011.74 (2011). Chesney, E., Goodwin, G. M. & Fazel, S. Risks of all-cause and suicide mortality in mental disorders: a meta-review. World Psychiatry 13 , 153-160, doi:10.1002/wps.20128 (2014). Moskowitz, L. & Weiselberg, E. Anorexia Nervosa/Atypical Anorexia Nervosa. Curr Probl Pediatr Adolesc Health Care 47 , 70-84, doi:10.1016/j.cppeds.2017.02.003 (2017). Paolacci, S. et al. Genetic contributions to the etiology of anorexia nervosa: New perspectives in molecular diagnosis and treatment. Mol Genet Genomic Med 8 , e1244, doi:10.1002/mgg3.1244 (2020). Yao, S. et al. Familial Liability for Eating Disorders and Suicide Attempts: Evidence From a Population Registry in Sweden. JAMA Psychiatry 73 , 284-291, doi:10.1001/jamapsychiatry.2015.2737 (2016). Zipfel, S., Lowe, B., Reas, D. L., Deter, H. C. & Herzog, W. Long-term prognosis in anorexia nervosa: lessons from a 21-year follow-up study. Lancet 355 , 721-722, doi:10.1016/S0140-6736(99)05363-5 (2000). Bulik, C. M. et al. Genetics and neurobiology of eating disorders. Nat Neurosci 25 , 543-554, doi:10.1038/s41593-022-01071-z (2022). Watson, H. J. et al. Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. Nat Genet 51 , 1207-1214, doi:10.1038/s41588-019-0439-2 (2019). Friedman, J. M. Leptin and the endocrine control of energy balance. Nat Metab 1 , 754-764, doi:10.1038/s42255-019-0095-y (2019). Hinney, A., Volckmar, A. L. & Antel, J. Genes and the hypothalamic control of metabolism in humans. Best Pract Res Clin Endocrinol Metab 28 , 635-647, doi:10.1016/j.beem.2014.04.007 (2014). Jais, A. & Bruning, J. C. Hypothalamic inflammation in obesity and metabolic disease. J Clin Invest 127 , 24-32, doi:10.1172/JCI88878 (2017). Hinney, A., Korner, A. & Fischer-Posovszky, P. The promise of new anti-obesity therapies arising from knowledge of genetic obesity traits. Nat Rev Endocrinol , doi:10.1038/s41574-022-00716-0 (2022). Loos, R. J. F. & Yeo, G. S. H. The genetics of obesity: from discovery to biology. Nat Rev Genet , doi:10.1038/s41576-021-00414-z (2021). Montague, C. T. et al. Congenital leptin deficiency is associated with severe early-onset obesity in humans. Nature 387 , 903-908, doi:10.1038/43185 (1997). Gibson, W. T. et al. Congenital leptin deficiency due to homozygosity for the Delta133G mutation: report of another case and evaluation of response to four years of leptin therapy. J Clin Endocrinol Metab 89 , 4821-4826, doi:10.1210/jc.2004-0376 (2004). Fatima, W. et al. Leptin deficiency and leptin gene mutations in obese children from Pakistan. Int J Pediatr Obes 6 , 419-427, doi:10.3109/17477166.2011.608431 (2011). Saeed, S., Butt, T. A., Anwer, M., Arslan, M. & Froguel, P. High prevalence of leptin and melanocortin-4 receptor gene mutations in children with severe obesity from Pakistani consanguineous families. Mol Genet Metab 106 , 121-126, doi:10.1016/j.ymgme.2012.03.001 (2012). Mazen, I., El-Gammal, M., Abdel-Hamid, M. & Amr, K. A novel homozygous missense mutation of the leptin gene (N103K) in an obese Egyptian patient. Mol Genet Metab 97 , 305-308, doi:10.1016/j.ymgme.2009.04.002 (2009). Wabitsch, M. et al. Severe Early-Onset Obesity Due to Bioinactive Leptin Caused by a p.N103K Mutation in the Leptin Gene. J Clin Endocrinol Metab 100 , 3227-3230, doi:10.1210/jc.2015-2263 (2015). Geller, F. et al. Melanocortin-4 receptor gene variant I103 is negatively associated with obesity. Am J Hum Genet 74 , 572-581, doi:10.1086/382490 (2004). Lotta, L. A. et al. Human Gain-of-Function MC4R Variants Show Signaling Bias and Protect against Obesity. Cell 177 , 597-607 e599, doi:10.1016/j.cell.2019.03.044 (2019). Rojo, D., McCarthy, C., Raingo, J. & Rubinstein, M. Mouse models for V103I and I251L gain of function variants of the human MC4R display decreased adiposity but are not protected against a hypercaloric diet. Mol Metab 42 , 101077, doi:10.1016/j.molmet.2020.101077 (2020). Hinney, A. et al. Evidence for three genetic loci involved in both anorexia nervosa risk and variation of body mass index. Mol Psychiatry 22 , 321-322, doi:10.1038/mp.2016.126 (2017). Zheng, Y. et al. PTBP2 - a gene with relevance for both Anorexia nervosa and body weight regulation. Transl Psychiatry 12 , 241, doi:10.1038/s41398-022-02018-5 (2022). Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat Genet 47 , 1236-1241, doi:10.1038/ng.3406 (2015). Seitz, J. et al. Leptin levels in patients with anorexia nervosa following day/inpatient treatment do not predict weight 1 year post-referral. Eur Child Adolesc Psychiatry 25 , 1019-1025, doi:10.1007/s00787-016-0819-4 (2016). Haas, V. et al. Leptin and body weight regulation in patients with anorexia nervosa before and during weight recovery. Am J Clin Nutr 81 , 889-896, doi:10.1093/ajcn/81.4.889 (2005). Hebebrand, J. et al. Leptin levels in patients with anorexia nervosa are reduced in the acute stage and elevated upon short-term weight restoration. Mol Psychiatry 2 , 330-334, doi:10.1038/sj.mp.4000282 (1997). Hebebrand, J. et al. The role of hypoleptinemia in the psychological and behavioral adaptation to starvation: Implications for anorexia nervosa. Neurosci Biobehav Rev 141 , 104807, doi:10.1016/j.neubiorev.2022.104807 (2022). Peters, T. et al. Suggestive Evidence for Causal Effect of Leptin Levels on Risk for Anorexia Nervosa: Results of a Mendelian Randomization Study. Front Genet 12 , 733606, doi:10.3389/fgene.2021.733606 (2021). Milos, G. et al. Short-term metreleptin treatment of patients with anorexia nervosa: rapid on-set of beneficial cognitive, emotional, and behavioral effects. Transl Psychiatry 10 , 303, doi:10.1038/s41398-020-00977-1 (2020). Antel, J. et al. Rapid amelioration of anorexia nervosa in a male adolescent during metreleptin treatment including recovery from hypogonadotropic hypogonadism. Eur Child Adolesc Psychiatry 31 , 1573-1579, doi:10.1007/s00787-021-01778-7 (2022). Gradl-Dietsch, G. et al. Rapid Emergence of Appetite and Hunger Resulting in Weight Gain and Improvement of Eating Disorder Symptomatology during and after Short-Term Off-Label Metreleptin Treatment of a Patient with Anorexia Nervosa. Obes Facts 16 , 99-107, doi:10.1159/000527386 (2023). Ehrlich, S. et al. Promoter specific DNA methylation and gene expression of POMC in acutely underweight and recovered patients with anorexia nervosa. J Psychiatr Res 44 , 827-833, doi:10.1016/j.jpsychires.2010.01.011 (2010). Hinney, A. et al. No evidence for involvement of the leptin gene in anorexia nervosa, bulimia nervosa, underweight or early onset extreme obesity: identification of two novel mutations in the coding sequence and a novel polymorphism in the leptin gene linked upstream region. Mol Psychiatry 3 , 539-543, doi:10.1038/sj.mp.4000394 (1998). Yilmaz, Z. et al. The role of leptin, melanocortin, and neurotrophin system genes on body weight in anorexia nervosa and bulimia nervosa. J Psychiatr Res 55 , 77-86, doi:10.1016/j.jpsychires.2014.04.005 (2014). Pulit, S. L. et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum Mol Genet 28 , 166-174, doi:10.1093/hmg/ddy327 (2019). Hinney, A. et al. Several mutations in the melanocortin-4 receptor gene including a nonsense and a frameshift mutation associated with dominantly inherited obesity in humans. J Clin Endocrinol Metab 84 , 1483-1486, doi:10.1210/jcem.84.4.5728 (1999). Steinhaus, R. et al. MutationTaster2021. Nucleic Acids Res 49 , W446-W451, doi:10.1093/nar/gkab266 (2021). Bendl, J. et al. PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions. PLoS Comput Biol 12 , e1004962, doi:10.1371/journal.pcbi.1004962 (2016). Yaghootkar, H. et al. Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity. Diabetes 69 , 2806-2818, doi:10.2337/db20-0070 (2020). Friedlander, Y. et al. Candidate molecular pathway genes related to appetite regulatory neural network, adipocyte homeostasis and obesity: results from the CARDIA Study. Ann Hum Genet 74 , 387-398, doi:10.1111/j.1469-1809.2010.00596.x (2010). Stutzmann, F. et al. Non-synonymous polymorphisms in melanocortin-4 receptor protect against obesity: the two facets of a Janus obesity gene. Hum Mol Genet 16 , 1837-1844, doi:10.1093/hmg/ddm132 (2007). Paisdzior, S. et al. Differential Signaling Profiles of MC4R Mutations with Three Different Ligands. Int J Mol Sci 21 , doi:10.3390/ijms21041224 (2020). Brouwers, B. et al. Human MC4R variants affect endocytosis, trafficking and dimerization revealing multiple cellular mechanisms involved in weight regulation. Cell Rep 34 , 108862, doi:10.1016/j.celrep.2021.108862 (2021). Hinney, A. et al. Melanocortin-4 receptor gene: case-control study and transmission disequilibrium test confirm that functionally relevant mutations are compatible with a major gene effect for extreme obesity. J Clin Endocrinol Metab 88 , 4258-4267, doi:10.1210/jc.2003-030233 (2003). Gu, W. et al. Identification and functional analysis of novel human melanocortin-4 receptor variants. Diabetes 48 , 635-639, doi:10.2337/diabetes.48.3.635 (1999). Ho, G. & MacKenzie, R. G. Functional characterization of mutations in melanocortin-4 receptor associated with human obesity. J Biol Chem 274 , 35816-35822, doi:10.1074/jbc.274.50.35816 (1999). Thearle, M. S. et al. Greater impact of melanocortin-4 receptor deficiency on rates of growth and risk of type 2 diabetes during childhood compared with adulthood in Pima Indians. Diabetes 61 , 250-257, doi:10.2337/db11-0708 (2012). Melchior, C. et al. Clinical and functional relevance of melanocortin-4 receptor variants in obese German children. Horm Res Paediatr 78 , 237-246, doi:10.1159/000343816 (2012). Rovite, V. et al. The role of common and rare MC4R variants and FTO polymorphisms in extreme form of obesity. Mol Biol Rep 41 , 1491-1500, doi:10.1007/s11033-013-2994-4 (2014). Nijenhuis, W. A., Garner, K. M., van Rozen, R. J. & Adan, R. A. Poor cell surface expression of human melanocortin-4 receptor mutations associated with obesity. J Biol Chem 278 , 22939-22945, doi:10.1074/jbc.M211326200 (2003). Xiang, Z. et al. Pharmacological characterization of 40 human melanocortin-4 receptor polymorphisms with the endogenous proopiomelanocortin-derived agonists and the agouti-related protein (AGRP) antagonist. Biochemistry 45 , 7277-7288, doi:10.1021/bi0600300 (2006). Valli-Jaakola, K. et al. Identification and characterization of melanocortin-4 receptor gene mutations in morbidly obese finnish children and adults. J Clin Endocrinol Metab 89 , 940-945, doi:10.1210/jc.2003-031182 (2004). Fischer-Posovszky, P. et al. A new missense mutation in the leptin gene causes mild obesity and hypogonadism without affecting T cell responsiveness. J Clin Endocrinol Metab 95 , 2836-2840, doi:10.1210/jc.2009-2466 (2010). Farooqi, I. S. et al. Clinical spectrum of obesity and mutations in the melanocortin 4 receptor gene. N Engl J Med 348 , 1085-1095, doi:10.1056/NEJMoa022050 (2003). Saeed, S. et al. Genetic variants in LEP, LEPR, and MC4R explain 30% of severe obesity in children from a consanguineous population. Obesity (Silver Spring) 23 , 1687-1695, doi:10.1002/oby.21142 (2015). Murray, P. G. et al. Reduced appetite and body mass index with delayed puberty in a mother and son: association with a rare novel sequence variant in the leptin gene. Eur J Endocrinol 164 , 521-527, doi:10.1530/EJE-10-0656 (2011). Dubern, B. et al. Mutational analysis of melanocortin-4 receptor, agouti-related protein, and alpha-melanocyte-stimulating hormone genes in severely obese children. J Pediatr 139 , 204-209, doi:10.1067/mpd.2001.116284 (2001). Heid, I. M. et al. Association of the 103I MC4R allele with decreased body mass in 7937 participants of two population based surveys. J Med Genet 42 , e21, doi:10.1136/jmg.2004.027011 (2005). Hebebrand, J., Muller, T. D., Holtkamp, K. & Herpertz-Dahlmann, B. The role of leptin in anorexia nervosa: clinical implications. Mol Psychiatry 12 , 23-35, doi:10.1038/sj.mp.4001909 (2007). Wabitsch, M. et al. Biologically inactive leptin and early-onset extreme obesity. N Engl J Med 372 , 48-54, doi:10.1056/NEJMoa1406653 (2015). Hebebrand, J. et al. Plasma concentrations of obese protein in anorexia nervosa. Lancet 346 , 1624-1625, doi:10.1016/s0140-6736(95)91955-4 (1995). Fan, Z. C. & Tao, Y. X. Functional characterization and pharmacological rescue of melanocortin-4 receptor mutations identified from obese patients. J Cell Mol Med 13 , 3268-3282, doi:10.1111/j.1582-4934.2009.00726.x (2009). Hebebrand, J. et al. Genetic predisposition to obesity in bulimia nervosa: a mutation screen of the melanocortin-4 receptor gene. Mol Psychiatry 7 , 647-651, doi:10.1038/sj.mp.4001053 (2002). Hunt, S. C. et al. Association of the FTO gene with BMI. Obesity (Silver Spring) 16 , 902-904, doi:10.1038/oby.2007.126 (2008). Hotta, K. et al. Variations in the FTO gene are associated with severe obesity in the Japanese. J Hum Genet 53 , 546-553, doi:10.1007/s10038-008-0283-1 (2008). Muller, T. D. et al. Fat mass and obesity-associated gene (FTO) in eating disorders: evidence for association of the rs9939609 obesity risk allele with bulimia nervosa and anorexia nervosa. Obes Facts 5 , 408-419, doi:10.1159/000340057 (2012). Genis-Mendoza, A. D. et al. Interaction of FTO rs9939609 and the native American-origin ABCA1 p.Arg230Cys with circulating leptin levels in Mexican adolescents diagnosed with eating disorders: Preliminary results. Psychiatry Res 291 , 113270, doi:10.1016/j.psychres.2020.113270 (2020). Niroula, A. & Vihinen, M. How good are pathogenicity predictors in detecting benign variants? PLoS Comput Biol 15 , e1006481, doi:10.1371/journal.pcbi.1006481 (2019). Pshennikova, V. G. et al. Comparison of Predictive In Silico Tools on Missense Variants in GJB2, GJB6, and GJB3 Genes Associated with Autosomal Recessive Deafness 1A (DFNB1A). ScientificWorldJournal 2019 , 5198931, doi:10.1155/2019/5198931 (2019). Cubuk, C. et al. Clinical likelihood ratios and balanced accuracy for 44 in silico tools against multiple large-scale functional assays of cancer susceptibility genes. Genet Med 23 , 2096-2104, doi:10.1038/s41436-021-01265-z (2021). Flanagan, S. E., Patch, A. M. & Ellard, S. Using SIFT and PolyPhen to predict loss-of-function and gain-of-function mutations. Genet Test Mol Biomarkers 14 , 533-537, doi:10.1089/gtmb.2010.0036 (2010). Cartegni, L., Wang, J., Zhu, Z., Zhang, M. Q. & Krainer, A. R. ESEfinder: A web resource to identify exonic splicing enhancers. Nucleic Acids Res 31 , 3568-3571, doi:10.1093/nar/gkg616 (2003). Tang, H. & Thomas, P. D. PANTHER-PSEP: predicting disease-causing genetic variants using position-specific evolutionary preservation. Bioinformatics 32 , 2230-2232, doi:10.1093/bioinformatics/btw222 (2016). Parthiban, V., Gromiha, M. M. & Schomburg, D. CUPSAT: prediction of protein stability upon point mutations. Nucleic Acids Res 34 , W239-242, doi:10.1093/nar/gkl190 (2006). Sim, N. L. et al. SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res 40 , W452-457, doi:10.1093/nar/gks539 (2012). Zhang, F. et al. Crystal structure of the obese protein leptin-E100. Nature 387 , 206-209, doi:10.1038/387206a0 (1997). Israeli, H. et al. Structure reveals the activation mechanism of the MC4 receptor to initiate satiation signaling. Science 372 , 808-814, doi:10.1126/science.abf7958 (2021). Allot, A. et al. LitVar: a semantic search engine for linking genomic variant data in PubMed and PMC. Nucleic Acids Res 46 , W530-W536, doi:10.1093/nar/gky355 (2018). Additional Declarations No competing interests reported. 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10:29:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3850003/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3850003/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-57517-w","type":"published","date":"2024-03-25T01:13:45+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53433891,"identity":"5665d933-b7ec-407e-b00b-2c3097550d04","added_by":"auto","created_at":"2024-03-26 01:13:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":380889,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3850003/v1/f5b2eca1-1ed6-4c27-b7c1-1d4125f99605.pdf"},{"id":49536791,"identity":"76d08f5a-3601-4dbd-8d65-a93e12524cde","added_by":"auto","created_at":"2024-01-12 16:17:03","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1198336,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3850003/v1/e692c9d32b21fcb96143b48f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unexpected identification of obesity-associated mutations in LEP and MC4R genes in patients with anorexia nervosa","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAnorexia nervosa (AN) is marked by a diminished body weight, a pronounced fear of gaining weight and a distorted body image\u003csup\u003e1\u003c/sup\u003e. Among psychiatric disorders, AN exhibits the highest mortality rates\u003csup\u003e2\u0026ndash;7\u003c/sup\u003e. Formal genetic studies revealed a robust genetic component for AN. In fact, twin-based studies have estimated a heritability for AN between 28 and 74%, depending on stringency of its definition and sample size\u003csup\u003e8\u003c/sup\u003e. In the last decade, genome-wide association studies (GWAS) uncovered eight genetic loci associated with AN\u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEnergy homeostasis and consequently, body weight regulation, are modulated by the leptin-melanocortin-system exerting its functions in the hypothalamus. Leptin (LEP) is secreted by the adipose tissue (AT) and relays adaptive signals about the mass of the AT and the nutritional status to the brain. In the hypothalamic arcuate nucleus, leptin binds to the leptin receptor leading to the inhibition of the orexigenic agouti-related peptide (AgRP)/neuropeptide Y (NPY) neurons, while stimulating the anorexigenic pro-opiomelanocortin (POMC)/cocaine and amphetamine regulated transcript (CART) neurons. The released POMC is post-transcriptionally processed into α-melanocyte-stimulating hormone (α-MSH), which subsequently bind to the melanocortin-4-receptor (MC4R). The resultant activation of MC4R leads to the production of satiety signals and consequently to a lower food intake and higher energy expenditure\u003csup\u003e10\u0026ndash;12,13\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDisruption of this regulation by loss of function (LoF) variants is known to be associated with severe monogenic forms of obesity \u003csup\u003e13,14\u003c/sup\u003e. The variants include non-synonymous and nonsense \u003cem\u003eLEP\u003c/em\u003e variants\u003csup\u003e15\u0026ndash;20\u003c/sup\u003e. Yet, gain of function (GoF) variants, e.g. in \u003cem\u003eMC4R\u003c/em\u003e\u003csup\u003e21\u0026ndash;23\u003c/sup\u003e, predispose to a lower body mass index (BMI). Further, previous studies have reported shared genetic loci for reduced BMI and AN risk\u003csup\u003e24\u0026ndash;26\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGenerally, patients with acute AN have considerably reduced serum leptin levels compared to BMI-matched controls. An increase in weight is accompanied by an increase in leptin \u003csup\u003e27\u0026ndash;29,30\u003c/sup\u003e. Besides, a Mendelian randomization study concluded that low leptin levels are correlated with a higher risk of AN\u003csup\u003e31\u003c/sup\u003e. Treating patients with AN off-label with recombinant leptin improved cognition, behaviour and mood\u003csup\u003e32\u0026ndash;34\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDespite emerging evidence for the crucial role of the leptin-melanocortin system in the aetiology of AN\u003csup\u003e31,35\u003c/sup\u003e, no associations of variants in \u003cem\u003eLEP\u003c/em\u003e in patients with AN have been described so far\u003csup\u003e9,36,37\u003c/sup\u003e. In \u003cem\u003eMC4R\u003c/em\u003e, the mutant allele of the variant rs2229616 was previously shown to have a BMI-decreasing effect \u003csup\u003e21,38\u003c/sup\u003e. Previously, we have screened both genes in rather small study groups of patients with AN\u003csup\u003e36,39\u003c/sup\u003e. In the present study, we expanded our previous findings by Sanger sequencing of the coding regions of \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e in larger study groups comprising 462 acutely ill or recovered women with AN and 445 healthy-lean controls. Based on \u003cem\u003ein silico\u003c/em\u003e analyses and previously published \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e data, we subsequently assessed the functional consequences of the detected variants.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eVariants in the coding regions of\u003c/strong\u003e \u003cstrong\u003eLEP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sequencing of the coding region of \u003cem\u003eLEP\u003c/em\u003e revealed a total of four rare (minor allele frequency (MAF)\u0026thinsp;\u0026le;\u0026thinsp;0.01%) variants (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). All identified carriers are heterozygous for the respective variant.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003ePhenotypic characteristics of the investigated study groups.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\u003ccolgroup\u003e\u003c/colgroup\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSample\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eStatus\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003en\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e% female\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAge in years\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eBMI in kg/m\u0026sup2;\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eBMI-SDS\u003csub\u003eLMS\u003c/sub\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003ePatients with AN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal cases\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e462\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e100\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e20.83 (8.63)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e16.48 (2.77)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e-2.55 (1.58)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAcutely ill\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e368\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e100\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e19.31 (7.70)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e15.43 (1.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e-2.99 (1.40)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRecovered\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e100\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e26.76 (9.42)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e20.57 (2.40)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e-0.82 (0.90)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHealthy-lean individuals\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eControls\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e445\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e61.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e26.04 (5.77)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e18.08 (1.13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\"\u003e\n\u003cp\u003e-2.77 (0.58)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003eAll data is represented as mean (SD). BMI: body mass index. BMI-SDS\u003csub\u003eLMS\u003c/sub\u003e: body mass index standard deviation score. SD: standard deviation\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eMinor allele frequencies of the detected variants in \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eGene\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eVariant\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eReference allele\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eMinor allele\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAmino acid exchange\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003ePatients with AN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eHealthy-lean individuals\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEuropean females in gnomAD\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMAF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMAF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMAF\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eLEP\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers201523305\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCys7=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e461\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e445\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers13306517\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGln25=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e462\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e444\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0009\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo rsID\u003c/p\u003e\n\u003cp\u003eg.128254532\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSer91=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e461\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e445\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers17151919\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVal94Met\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e461\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e445\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"8\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eMC4R\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers121913557\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVal50Leu\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e461\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e444\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers2229616\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVal103Ile\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e447\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e432\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers13447329\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThr112Met\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e461\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e443\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers13447331\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSer127Leu\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e461\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e445\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNovel variant\u003c/p\u003e\n\u003cp\u003eg.60371891\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTyr153=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e461\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e445\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo rsID\u003c/p\u003e\n\u003cp\u003eg.60371771\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVal193=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e462\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e444\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers13447338\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGAGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLeu211fsX\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e461\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e445\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.00002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers52820871\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIle251Leu\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e456\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.006\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e437\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.009\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.01\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"14\"\u003eHere, all detected variants in the coding regions of \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e are represented for the respective study groups. The alleles are assigned based on the forward strand. Additionally, the minor allele frequency of the non-Finnish European females in the Genome Aggregation Database (gnomAD) for each SNP is given. Some genetic variants are not represented in the used version (v2.1.1) of gnomAD (\u003cem\u003eNA\u003c/em\u003e). 11: homozygous wildtype. 12: heterozygous. 22: homozygous minor allele. gnomAD: Genome Aggregation Database. MAF: minor allele frequency. \u003cem\u003eNA\u003c/em\u003e: not available.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eOne variant led to a non-conservative amino acid exchange (rs17151919, p.Val94Met), while all others were synonymous variants (rs201523305, p.Cys7=; rs13306517, p.Gln25\u0026thinsp;=\u0026thinsp;and a variant without an rsID, p.Ser91=). The non-synonymous variant (rs17151919) was detected in the heterozygous state in an acutely ill female patient with AN (age: 34.12 years old; BMI: 15.94 kg/m\u0026sup2;; BMI-SDS\u003csub\u003eLMS\u003c/sub\u003e: -3.62). \u003cem\u003eIn silico\u003c/em\u003e tools, like MutationTaster2021\u003csup\u003e40\u003c/sup\u003eand PredictSNP2\u003csup\u003e41\u003c/sup\u003e, hinted at an overall non-pathogenic effect. Yet, the resultant amino acid substitution was predicted to have a destabilizing impact on LEP (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The mutant allele (Met94; in mature protein this equals position 73; see Supplementary Fig.\u0026nbsp;1) was already reported to be associated with lower leptin levels and a higher childhood BMI in individuals of African ancestry\u003csup\u003e42\u003c/sup\u003e. At baseline, each mutant allele added approximately 2.6 kg to the carrier\u0026rsquo;s weight, while the weight increased to 4.8 kg at year 20\u003csup\u003e43\u003c/sup\u003e. No associations were detected in Europeans, as this variant was extremely rare in this population\u003csup\u003e42\u003c/sup\u003e. Functional \u003cem\u003ein vitro\u003c/em\u003e analyses reported a decreased leptin secretion in human embryonic kidney 293 cells caused by the substitution of valine by methionine\u003csup\u003e42\u003c/sup\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003e\u003cem\u003eIn silico\u003c/em\u003e analyses for the detected variants in \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eGene\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eVariant\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eAmino acid exchange\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003ePredictions for all variants\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003ePredictions for non-synonymous variants\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eESEfinder\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMutation\u003c/p\u003e\n\u003cp\u003eTaster2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePredictSNP2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePANTHER-PSEP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eCUPSAT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSIFT\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSplice site\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrediction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrediction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrediction\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eStability\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTorsion\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrediction\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eLEP\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers201523305\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCys7=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChanged\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBenign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeutral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers13306517\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGln25=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNot changed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBenign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeutral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo rsID\u003c/p\u003e\n\u003cp\u003eg.128254532C/T\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSer91=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNot changed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBenign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeutral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers17151919\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVal94Met\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNot changed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBenign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeutral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eProbably benign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDestabilizing\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFavourable\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTolerated\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"8\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eMC4R\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers121913557\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVal50Leu\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChanged\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDeleterious\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDeleterious\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eProbably benign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDestabilizing\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFavourable\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDeleterious\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers2229616\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVal103Ile\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChanged\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBenign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDeleterious\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eProbably benign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDestabilizing\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFavourable\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTolerated\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers13447329\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eThr112Met\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChanged\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBenign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeutral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eProbably benign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTolerated\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers13447331\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSer127Leu\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChanged\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDeleterious\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDeleterious\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eProbably damaging\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eStabilizing\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFavourable\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTolerated\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNovel variant\u003c/p\u003e\n\u003cp\u003eg.60371891A/G\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTyr153=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChanged\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBenign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeutral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo rsID\u003c/p\u003e\n\u003cp\u003eg.60371771G/A\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVal193=\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNot changed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBenign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeutral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers13447338\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLeu211fsX\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChanged\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ers52820871\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIle251Leu\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChanged\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBenign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeutral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eProbably benign\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDestabilizing\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFavourable\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTolerated\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"10\"\u003eTo predict putative effects of the mutant alleles, various \u003cem\u003ein silico\u003c/em\u003e tools were applied. Putative impacts on splicing products were examined with the tool ESEfinder (\u003csup\u003e75\u003c/sup\u003e). The general pathogenicity was predicted with MutationTaster2021 (\u003csup\u003e40\u003c/sup\u003e) and PredictSNP2 (\u003csup\u003e41\u003c/sup\u003e). The latter being a consensus classifier condensing results of multiple tools, like CADD and FATHMM. Indications for impacts on the proteins were investigated with PANTHER-PSEP (\u003csup\u003e76\u003c/sup\u003e), CUPSAT (\u003csup\u003e77\u003c/sup\u003e) and SIFT (\u003csup\u003e78\u003c/sup\u003e). Tools predicting effects on the protein were only applicable for non-synonymous variants. Yet, as the used protein reference sequence of MC4R was incomplete, the non-synonymous variant rs13447329 (p.Thr112Met) could not be analysed with CUPSAT and SIFT.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eMoreover, three synonymous variants rs201523305 (p.Cys7=), rs13306517 (p.Gln25=) and a variant without an assigned rsID (p.Ser91=) were determined (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The latter variant (p.Ser91=) had already been detected in our previous mutation screen\u003csup\u003e36\u003c/sup\u003e. One recovered patient with AN (BMI: 21.23 kg/m\u0026sup2;; BMI-SDS\u003csub\u003eLMS\u003c/sub\u003e: -1.11) harboured the variant rs201523305 (p.Cys7=) predicted to alter splice sites (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The variant leading to p.Ser91\u0026thinsp;=\u0026thinsp;was found in one acutely ill adolescent with AN (BMI: 15.43 kg/m\u0026sup2;; BMI-SDS\u003csub\u003eLMS\u003c/sub\u003e: \u0026minus;\u0026thinsp;3.03). Again, \u003cem\u003ein silico\u003c/em\u003e tools hinted at a benign impact (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The variant rs13306517 (p.Gln25=) was exclusively detected in one lean control individual (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). This variant was implied not to have functional implications (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Beyond, no functional studies have previously been published for these variants (see Supplementary Tables\u0026nbsp;2 and 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVariants in the coding region of\u003c/strong\u003e \u003cstrong\u003eMC4R\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEight variants located in the coding sequence of \u003cem\u003eMC4R\u003c/em\u003e were identified (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Five of those are non-synonymous variants (rs121913557, p.Val50Leu; rs2229616, p.Val103Ile; rs13447329, p.Thr112Met; rs13447331, p.Ser127Leu; rs52820871, p.Ile251Leu; for structural positions of non-synonymous variants see Supplementary Fig.\u0026nbsp;2). Additionally, one frameshift (rs13447338, p.Leu211\u003cem\u003efs\u003c/em\u003eX), one novel synonymous (p.Tyr153=) and one synonymous variant without an assigned rsID (p.Val193=) were determined (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eWe observed the non-synonymous variants rs2229616 (p.Val103Ile) and rs52820871 (p.Ile251Leu) in similar frequencies in our 462 patients with AN, and 445 healthy-lean controls (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Our \u003cem\u003ein silico\u003c/em\u003e analyses hinted at a putative deleterious effect caused by rs2229616 without affecting splice sites and the protein\u0026rsquo;s torsion, while rs52828071 was predicted to be overall benign but has the potential to destabilize MC4R (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Numerous studies have already reported a reduced risk for obesity and an association with a lower BMI of the infrequent alleles of rs2229616 and rs52820871\u003csup\u003e22,21,44\u003c/sup\u003e. In 2004, Geller and colleagues detected a reduced transmission rate of the Ile103 allele in an analysis of family-based samples, thus providing initial evidence for an obesity-protective effect of this variant \u003csup\u003e21\u003c/sup\u003e. Functional implications of both frequent variants have been thoroughly studied, as well. For instance, the introduction of the variants in inbred mice, showed no significant difference in food intake and BMI between homozygous or heterozygous mice for each mutant and their wildtype (WT) littermates. Yet, homozygous female mice (\u003cem\u003eMC4R\u003c/em\u003e\u003csup\u003eV103I/V103I\u003c/sup\u003e and \u003cem\u003eMC4R\u003c/em\u003e\u003csup\u003eI251L/I251L\u003c/sup\u003e) had a reduced longitudinal length and their white adipose tissue weighed less in relation to their WT littermates. Albeit, when fed a high-fat diet, these mice\u0026rsquo;s adiposity resembled those of their littermates not carrying a variant\u003csup\u003e23\u003c/sup\u003e. Another study showed that variants p.Val103Ile and p.Ile251Leu can be characterised as GoF variants as they have a significant bias towards the \u0026szlig;-arrestin recruitment rather than cyclic adenosine monophosphate (cAMP)-mediated signalling. Beyond, it was determined that the MC4R carrying the mutant Ile103 allele did not internalize like the WT MC4R and consequently exhibited a stable expression on the cell surface upon agonist stimulation\u003csup\u003e22\u003c/sup\u003e. In accordance, another study supported a deviating signalling behaviour due to p.Val103Ile yielding in GoF characteristics\u003csup\u003e45\u003c/sup\u003e. Conflicting to these findings, others reported that both variants displayed an elevated presence at the plasma membrane. Upon agonist stimulation, solely p.Ile251Leu led to a reduced internalisation, while the MC4R with the mutant Ile103 allele maintained an unaltered internalisation\u003csup\u003e46\u003c/sup\u003e. Besides, multiple studies did not ascertain any functional differences between the WT and mutant MC4R for p.Val103Ile and p.Ile251Leu\u003csup\u003e21,47\u0026ndash;50\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWe further have detected one lean control individual (BMI: 17.00 kg/m\u0026sup2;; BMI-SDS: -2.64) harbouring two frequent variants leading to p.Val103Ile and p.Ile251Leu. Similarly, one patient with AN carried the common rs2229616 (p.Val103Ile) and the rare variant rs13447331 (p.Ser127Leu). This patient had a restrictive AN. At admission the patient had a weight of 45.3 kg being 169.5 cm tall (BMI: 15.67 kg/m\u0026sup2;; 4th BMI-percentile). During the 19 weeks in-patient treatment 6 kg were gained resulting in a BMI of 17.75 kg/m\u0026sup2; at discharge. Leptin levels were 1.66 \u0026micro;g/l at admission and increased during treatment up to 5.59 \u0026micro;g/l at discharge. After 2.5 years, the patient had a BMI of 22.66 kg/m\u0026sup2; (weight: 66 kg), while leptin levels were 43.31 \u0026micro;g/l. \u003cem\u003eIn vitro\u003c/em\u003e studies on double mutant receptors with p.Val103Ile and p.Ser127Leu demonstrated that these can cause a reduced efficacy and potency\u003csup\u003e51\u003c/sup\u003e and are less abundant on cell surfaces\u003csup\u003e52\u003c/sup\u003e. An increase in the cAMP accumulation in relation to the single mutant MC4R carrying the Leu127 allele was determined\u003csup\u003e52\u003c/sup\u003e. We did not detect the rare variant leading to the non-conservative amino acid substitution from serine to leucine at position 127 in any additional individuals here (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). \u003cem\u003eIn silico\u003c/em\u003e tools detected functional implications for this variant, as it was rated as deleterious by MutationTaster2021 and PredictSNP2. Yet, no destabilizing potential on the MC4R protein was indicated (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe frameshift mutation in \u003cem\u003eMC4R\u003c/em\u003e (rs13447338) resulting in a truncated protein (p.Leu211fsX) was detected once in a female adolescent with AN, and not in the lean individuals (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The female patient with AN displayed the restrictive form of AN. At admission, she weighed 35.10 kg while being 161 cm tall (BMI: 13.54 kg/m\u0026sup2;; 0th BMI-percentile). During her 20-week in-patient treatment, she gained 13 kg. At discharge, she had a weight of 48.1 kg and a BMI of 18.56 kg/m\u0026sup2;. Leptin levels were 0.85 \u0026micro;g/l at admission and increased to 10.6 \u0026micro;g/l at discharge. After 2.5 years, the patient\u0026rsquo;s weight was 49 kg yielding in a BMI of 18.29 kg/m\u0026sup2;, while leptin levels were 6.61 \u0026micro;g/l. One \u003cem\u003ein vitro\u003c/em\u003e study validated the functional impact of the truncated protein reporting that this variant caused a complete loss-of-function\u003csup\u003e47\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe other two non-synonymous and rare variants rs121913557 (p.Val50Leu) and rs13447329 (p.Thr112Met) were detected in both study groups. While \u003cem\u003ein silico\u003c/em\u003e analyses hinted at a putative pathogenic and protein destabilizing impact of rs121913557, no functional implications for rs13447329 were detected (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Previous studies analysing rs13447329 effects \u003cem\u003ein vitro\u003c/em\u003e resulted in ambiguous findings. Thus, increased agonist potency and affinity for \u0026alpha;-MSH was detected\u003csup\u003e53,54\u003c/sup\u003e. The mutant receptor further showed a decrease in cell surface expression in comparison to the WT\u003csup\u003e53\u003c/sup\u003e. Yet, multiple studies reported no functional difference of the mutant MC4R caused by this variant and the WT receptor\u003csup\u003e48,51,55\u003c/sup\u003e. No functional studies have been performed for the Leut50 allele of rs121913557 so far (see Supplementary Tables\u0026nbsp;3, 4 and 5).\u003c/p\u003e\n\u003cp\u003eBoth synonymous variants identified (p.Tyr153\u0026thinsp;=\u0026thinsp;and p.Val193=) were detected each in one proband (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The variant p.Val193\u0026thinsp;=\u0026thinsp;was detected once in the lean control group and was implied to be benign (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The other synonymous and novel variant p.Tyr153\u0026thinsp;=\u0026thinsp;was found in one patient with AN (BMI: 17.29 kg/m\u0026sup2;). For this variant, \u003cem\u003ein silico\u003c/em\u003e tools revealed a high capacity to affect splicing and to be pathogenic (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Functional \u003cem\u003ein vitro\u003c/em\u003e studies were not available (see Supplementary Tables\u0026nbsp;3, 4 and 5).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eGenetic variants in genes of the leptin-melanocortin system, like \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e, are predominantly associated with monogenic forms of obesity\u003csup\u003e13,15,18,20,36,39,56\u0026ndash;58\u003c/sup\u003e. Reports emerged indicating that some variants in these genes also predispose to a lower BMI\u003csup\u003e21,22,59\u003c/sup\u003e. Genetic correlations between BMI, obesity and AN have been uncovered\u003csup\u003e9,24\u0026ndash;26\u003c/sup\u003e. In fact, genetic variants for AN are negatively correlated with BMI, leptin levels, body fat percentage, waist circumference, overweight as well as obesity\u003csup\u003e9,26\u003c/sup\u003e. Previously, we have identified nine SNPs at three independent genetic loci being associated with low BMI and AN\u003csup\u003e24\u003c/sup\u003e. To expand the findings of our previous mutation screens\u003csup\u003e36,39\u003c/sup\u003e, we have sequenced the coding regions of \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e in 462 female patients with AN, and 445 healthy-lean controls. Collectively, we have detected four variants in the \u003cem\u003eLEP\u003c/em\u003e gene and eight variants in \u003cem\u003eMC4R\u003c/em\u003e. Strikingly, we detected known variants leading to reduced or even loss-of-function which are associated with obesity \u003csup\u003e60,39\u003c/sup\u003e. Yet, the \u003cem\u003eMC4R\u003c/em\u003e-located variants rs2229616 (p.Val103Ile) and rs52820871 (p.Ile251Leu) detected in multiple patients with AN and healthy-lean controls were already known to be associated with a lower BMI and a reduced risk for obesity \u003csup\u003e21,22,44,61\u003c/sup\u003e. \u003cem\u003eIn silico\u003c/em\u003e analyses indicated largely benign effects, while certain variants in both genes might impact the stability or torsion of the respective protein.\u003c/p\u003e \u003cp\u003eThe relevance of the leptin-melanocortin system in body weight regulation, energy expenditure as well as AN is already known \u003csup\u003e10,29\u003c/sup\u003e. Patients with AN have reduced serum leptin levels, which typically rise as weight is restored\u003csup\u003e28,29\u003c/sup\u003e. Strikingly, low leptin levels were linked to AN hallmark characteristics, like hyperactivity and amenorrhea\u003csup\u003e62\u003c/sup\u003e. A recent Mendelian randomization study has reported that low leptin levels are correlated with a higher risk of AN. This correlation was also evident when analysing an exclusive female dataset. Notably, a correlation of AN with leptin levels was not detected\u003csup\u003e31,33,34\u003c/sup\u003e. Beyond, off-label treatment of patients with AN (case studies) with recombinant leptin helped to improve cognition, emotions, and behavioural traits, like hyperactivity and repetitive thoughts of food\u003csup\u003e32\u0026ndash;34\u003c/sup\u003e. Evidence for the involvement of leptin\u0026rsquo;s downstream target \u003cem\u003eMC4R\u003c/em\u003e in AN is mostly based on animal models. In fact, the activation of \u003cem\u003eMC4R\u003c/em\u003e in rats decreased food intake, while coincidently activating the hypothalamic-pituitary-adrenal axis. This activation eventually led to increased motor activity. It was suggested that genetic variants might trigger this coherence and thus lead to a prolonged stimulation of the leptin-melanocortin-system supporting the development of AN\u003csup\u003e5\u003c/sup\u003e. Thus, it is feasible that genetic variants in genes of the leptin-melanocortin system, especially as overlaps between genetic loci relevant for low BMI and AN are known\u003csup\u003e24,25\u003c/sup\u003e, impact the etiology of AN.\u003c/p\u003e \u003cp\u003eHowever, to date, no significant associations of genetic variants in these genes with AN were reported\u003csup\u003e36,37\u003c/sup\u003e. Due to our still limited sample size and generally low allele frequencies of the here detected variants, we were also unable to report associations with AN. Nevertheless, this study was able to expand our previously published mutation screens for both genes\u003csup\u003e36,39\u003c/sup\u003e. Our extended sample size enabled us to discover new variants in \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e, which potentially are relevant for AN. This emphasises the ongoing necessity for comprehensive large-scale genetic studies. Here, we did detect variants in \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e, which were previously described to cause a partial or even complete loss of function in humans when present in a homozygous state and were thus associated with severe forms of obesity\u003csup\u003e39,51,60\u003c/sup\u003e. For instance, in 1999, we have described the frameshift mutation (rs13447338) yielding in a truncated MC4R in one adolescent and her mother with severe obesity\u003csup\u003e39\u003c/sup\u003e. In the present study, we have detected the same frameshift variant in the heterozygous state in one patient with AN. Yet, as no premorbid weight data was available, it is feasible that this patient had premorbid obesity triggering the development of AN. Further, we have to note that pathogenic variants typically are present homozygously\u003csup\u003e15,63\u003c/sup\u003e. For heterozygous \u003cem\u003eMC4R\u003c/em\u003e variants, carrier develop obesity later in childhood\u003csup\u003e13\u003c/sup\u003e, while for heterozygous \u003cem\u003eLEP\u003c/em\u003e variants, carriers are mainly unaffected\u003csup\u003e15,63\u003c/sup\u003e. As we have exclusively detected heterozygous variants in both genes, the relevance remains unknown. Yet, one patient with AN was detected to harbour two variants simultaneously (rs2229616, p.Val103Ile and rs13447331, p.Ser127Leu). Leptin levels at admission were in the expected range\u003csup\u003e64\u003c/sup\u003e and increased during in-patient treatment. Yet, after 2.5 years, leptin levels were rather high (43.31 \u0026micro;g/l). The variant leading to p.Val103Ile is known to lead to an elevated function\u003csup\u003e21,22,46\u003c/sup\u003e, while the amino acid substitution of serine to leucine at the 127th position was described to lead to a LoF in the majority of parameters analysed\u003csup\u003e45,55,65\u003c/sup\u003e (see Supplementary Tables\u0026nbsp;3, 4 and 5). Notably, certain studies also indicated no functional deviations for mutant receptors with either Ile103 or Leu127\u003csup\u003e48,49,54\u003c/sup\u003e. Yet, functional studies for a double mutant MC4R showed for example a reduced efficacy and potency\u003csup\u003e51\u003c/sup\u003e. Previously, we have also detected weight reducing variants in \u003cem\u003eMC4R\u003c/em\u003e in patients with bulimia nervosa\u003csup\u003e66\u003c/sup\u003e. Further, the \u003cem\u003eFTO\u003c/em\u003e variant rs9939609 associated with obesity\u003csup\u003e67,68\u003c/sup\u003e was previously identified in patients with eating disorders\u003csup\u003e69,70\u003c/sup\u003e. Besides a nominal association with bulimia nervosa and anorexia nervosa\u003csup\u003e69\u003c/sup\u003e, a synergic effect of this variant on leptin levels with an another variant in \u003cem\u003eABCA1\u003c/em\u003e was described\u003csup\u003e70\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn addition, a number of studies demonstrated that two types of \u003cem\u003eMC4R\u003c/em\u003e variants exist which can be distinguished according to their distinct signalling behaviour\u003csup\u003e22,46\u003c/sup\u003e. For example, variants such as the rs13447329 (p.Thr112Met) detected here, are characterised by a LoF. Other variants, such as rs2229616 (p.Val103Ile), show a GoF phenotype\u003csup\u003e22,46\u003c/sup\u003e. The latter GoF variants are associated with a reduced risk for obesity and a lower BMI\u003csup\u003e21,22,44\u003c/sup\u003e. In fact, heterozygous carriers of GoF variants weighed on overage 0.39 kg/m\u0026sup2; less than non-carriers, while homozygotes even showed an average 0.88 kg/m\u0026sup2; decreased BMI\u003csup\u003e22\u003c/sup\u003e. Similarly, an animal model with transgenic mice expressing either Val103Ile or Ile251Leu exhibited GoF phenotypes. This was even more pronounced in female than male mice. For instance, female mice carrying the variant Val103Ile homozygous had a 40% lower abdominal white adipose tissue mass than their wildtype littermates. This difference was not detected in the male transgenic mice\u003csup\u003e23\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBased on our data, we are unable to deduce a mechanism explaining how these variants may have a relevance for the phenotypes at the extremes of the weight scale. Yet, a resembling mechanism of action, as \u003cem\u003eFTO\u003c/em\u003e\u0026rsquo;s rs9939609 is feasible\u003csup\u003e70\u003c/sup\u003e. Functional \u003cem\u003ein vitro\u003c/em\u003e studies under fasting and starvation conditions are needed to expand the findings of the general \u003cem\u003ein vitro\u003c/em\u003e data already published for each variant.\u003c/p\u003e \u003cp\u003eWe are aware that \u003cem\u003ein silico\u003c/em\u003e tools have their limitations and can vary substantially in their specificity\u003csup\u003e71\u0026ndash;73\u003c/sup\u003e. Particularly, predicting functional implications of GoF variants was found to be more challenging by various \u003cem\u003ein silico\u003c/em\u003e tools than finding an accurate implication for a LoF variant \u003csup\u003e74\u003c/sup\u003e. Hence, we have additionally checked the already published \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e data stated in LitVar\u0026sup2; and on the \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.mc4r.org.ukwebsite\" target=\"_blank\"\u003ewww.mc4r.org.ukwebsite\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.mc4r.org.ukwebsite\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Nevertheless, no clear-cut results were obtained for most of the variants (see Supplementary Tables\u0026nbsp;2, 3, 4 and 5). Presumably, this is due to variations in study design as well as the time period in which the studies were conducted. For example, older studies increasingly failed to detect any differences between WT and mutant MC4R. This was particularly evident for studies investigating the common GoF variant rs2229616 (p.Val103Ile) in \u003cem\u003eMC4R\u003c/em\u003e. Supposedly, this results from the technical advances and new experimental techniques implemented in recent years. In addition, there are many variants for which no or only very few functional studies have been completed. For example, only 16 studies have been conducted on the rs17151919 variant in the leptin gene, of which just one included functional \u003cem\u003ein vitro\u003c/em\u003e analyses (see Supplementary Table\u0026nbsp;2). Conversely, for the common variant rs2229616 in \u003cem\u003eMC4R\u003c/em\u003e, there are over 150 studies, of which numerous also present \u003cem\u003ein vitro\u003c/em\u003e or even \u003cem\u003ein vivo\u003c/em\u003e data (see Supplementary Tables\u0026nbsp;3, 4 and 5).\u003c/p\u003e \u003cp\u003eGiven the reported genetic overlaps between BMI and AN\u003csup\u003e9,24\u0026ndash;26\u003c/sup\u003e and GoF variants in \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e being associated with a lower BMI and a reduced odds for obesity\u003csup\u003e21\u0026ndash;23,59\u003c/sup\u003e, we have Sanger sequenced the coding regions of \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e in 462 female patients with AN and 445 healthy-lean controls. We have detected four variants in \u003cem\u003eLEP\u003c/em\u003e and eight variants in the coding sequence of \u003cem\u003eMC4R\u003c/em\u003e. Here we detected variants with a partial or complete LoF \u003cem\u003ein vitro\u003c/em\u003e in heterozygous patients with AN. Homozygous carriers of these variants typically develop obesity.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003eStudy groups\u003c/h2\u003e\n\u003cp\u003eTo detect variants in the coding regions of \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e, 462 female patients with AN (acutely ill or recovered; age: 20.83\u0026thinsp;\u0026plusmn;\u0026thinsp;8.63 years old; BMI: 16.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.77 kg/m\u0026sup2;; BMI-SDS\u003csub\u003eLMS\u003c/sub\u003e: \u0026minus;\u0026thinsp;2.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.58; see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) and 445 healthy-lean individuals without a diagnosed eating disorder (age: 26.04\u0026thinsp;\u0026plusmn;\u0026thinsp;5.77 years old; BMI: 18.08\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13 kg/m\u0026sup2;; BMI-SDS\u003csub\u003eLMS\u003c/sub\u003e: \u0026minus;\u0026thinsp;2.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58; see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) were included. In previous studies we have already screened 49 patients with AN for \u003cem\u003eLEP\u003c/em\u003e and 51 patients with AN and 25 lean individuals for \u003cem\u003eMC4R\u003c/em\u003e\u003csup\u003e36,39\u003c/sup\u003e. Written informed consent was given by all participants and in case of minors by their parents. This study was approved by the Ethics committee of the respective Universities and was performed in accordance with the \u003cem\u003eDeclaration of Helsinki\u003c/em\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003eMutation screen\u003c/h2\u003e\n\u003cp\u003eThe coding regions of \u003cem\u003eLEP\u003c/em\u003e (chr7: 128,241,278\u0026ndash;128,257,629; GRCh38; ENSG00000174697) and \u003cem\u003eMC4R\u003c/em\u003e (chr18: 60,371,062\u0026ndash;60,372,775; GRCh38; ENSG00000166603) were Sanger sequenced in 462 patients with AN, and 445 healthy-lean individuals (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) to detect genetic variants. These were identified by performing polymerase chain reactions (PCR; Veriti 96-well Thermal Cycler, Applied Biosystems, Foster City, CA, USA) with coding sequence specific primers (see Supplementary Table\u0026nbsp;1). PCR products were sent for sequencing to MicroSynth Seqlab GmbH (G\u0026ouml;ttingen, Germany). At least two independent scientists performed the sequence analysis and genotype assignment using the SeqMan Pro software (v.11.0.0, DNAstar Inc., Madison, WI, USA). Discrepancies were solved by either reaching consensus or by re-sequencing.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003eHardy-Weinberg-Equilibrium\u003c/h2\u003e\n\u003cp\u003eAll detected variants were checked for compliance with the Hardy-Weinberg-Equilibrium (HWE). All variants fulfilled the HWE.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn silico\u003c/strong\u003e \u003cstrong\u003eanalyses and assessment of functional implications by published data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo uncover putative functional implications of the detected variants, \u003cem\u003ein silico\u003c/em\u003e analyses applying various tools ensued. The detected variants were analysed pertaining their potential to alter splice sites (ESEfinder\u003csup\u003e75\u003c/sup\u003e) and their general pathogenicity (MutationTaster2021\u003csup\u003e40\u003c/sup\u003e; PredictSNP2\u003csup\u003e41\u003c/sup\u003e). Effects of non-synonymous variants on the protein structure of LEP or MC4R were examined using PANTHER-PSEP\u003csup\u003e76\u003c/sup\u003e, the Cologne University Protein Stability Analysis Tool\u003csup\u003e77\u003c/sup\u003e (CUPSAT) and the tool Sorting from Intolerant to Tolerant\u003csup\u003e78\u003c/sup\u003e (SIFT). The required protein structures were extracted from the Research Collaboratory for Structural Bioinformatics protein data bank (RCSB PDB): LEP (1AX8\u003csup\u003e79\u003c/sup\u003e) and MC4R (7AUE\u003csup\u003e80\u003c/sup\u003e).\u003c/p\u003e\n\u003cp\u003eTo extend the functional implications derived from the \u003cem\u003ein silico\u003c/em\u003e analyses with previously published \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e data, the LitVar\u0026sup2; \u003csup\u003e81\u003c/sup\u003e (accessed on Sep. 26th 2022) database was screened for each variant in \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e detected in this study. For \u003cem\u003eMC4R\u003c/em\u003e variants, the website \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.mc4r.org.ukwebsite\" target=\"_blank\"\u003ewww.mc4r.org.uk\u003c/a\u003e\u003c/span\u003e\u003c/span\u003e (accessed on Sep. 26th 2022) summarizing publications for each variant, was additionally analysed. This website is provided by the University of Cambridge Metabolic Research Laboratories. A complete list of all studies provided by LitVar\u0026sup2; and \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.mc4r.org.ukwebsite\" target=\"_blank\"\u003ewww.mc4r.org.uk\u003c/a\u003e\u003c/span\u003e\u003c/span\u003e can be found in the Supplementary Table\u0026nbsp;4.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all participants for their participation in our study. Further, we are indebted to Sieglinde D\u0026uuml;erkop for her excellent technical support. This study was funded by the Deutsche Forschungsgemeinschaft (DFG, HI 865/2-1, DFG Research Unit FOR2488), the BMBF (01GS0820; PALGER 2017-33: 01DH19010) and the Stiftung Universit\u0026auml;tsmedizin Essen.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBHD, JS, MdZ, Wh, SE, SZ, KG, KE, RB, MF, JH and AH recruited participants and provided the samples. LSR, YZ, PFP, JH and AH conceptualized the study. LSR and YZ performed the mutation screen and \u003cem\u003ein silico\u003c/em\u003e analyses. LSR, YZ, JA and AH interpreted the data. LSR did the database research and wrote the manuscript. All authors read and approved the submitted version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe generated and analysed Sanger-sequencing data are available from the corresponding author on reasonable request. Data which was extracted from public websites or databases are included in the Supplementary Information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author\u0026rsquo;s declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAssociation, A. P. \u003cem\u003eDiagnostic and Statistical Manual of Mental Disorders (DSM-5\u0026reg;)\u003c/em\u003e. (American Psychiatric Publishing, 2013).\u003c/li\u003e\n\u003cli\u003eArcelus, J., Mitchell, A. J., Wales, J. \u0026amp; Nielsen, S. Mortality rates in patients with anorexia nervosa and other eating disorders. A meta-analysis of 36 studies. \u003cem\u003eArch Gen Psychiatry\u003c/em\u003e \u003cstrong\u003e68\u003c/strong\u003e, 724-731, doi:10.1001/archgenpsychiatry.2011.74 (2011).\u003c/li\u003e\n\u003cli\u003eChesney, E., Goodwin, G. M. \u0026amp; Fazel, S. Risks of all-cause and suicide mortality in mental disorders: a meta-review. \u003cem\u003eWorld Psychiatry\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 153-160, doi:10.1002/wps.20128 (2014).\u003c/li\u003e\n\u003cli\u003eMoskowitz, L. \u0026amp; Weiselberg, E. Anorexia Nervosa/Atypical Anorexia Nervosa. \u003cem\u003eCurr Probl Pediatr Adolesc Health Care\u003c/em\u003e \u003cstrong\u003e47\u003c/strong\u003e, 70-84, doi:10.1016/j.cppeds.2017.02.003 (2017).\u003c/li\u003e\n\u003cli\u003ePaolacci, S.\u003cem\u003e et al.\u003c/em\u003e Genetic contributions to the etiology of anorexia nervosa: New perspectives in molecular diagnosis and treatment. \u003cem\u003eMol Genet Genomic Med\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, e1244, doi:10.1002/mgg3.1244 (2020).\u003c/li\u003e\n\u003cli\u003eYao, S.\u003cem\u003e et al.\u003c/em\u003e Familial Liability for Eating Disorders and Suicide Attempts: Evidence From a Population Registry in Sweden. \u003cem\u003eJAMA Psychiatry\u003c/em\u003e \u003cstrong\u003e73\u003c/strong\u003e, 284-291, doi:10.1001/jamapsychiatry.2015.2737 (2016).\u003c/li\u003e\n\u003cli\u003eZipfel, S., Lowe, B., Reas, D. L., Deter, H. C. \u0026amp; Herzog, W. Long-term prognosis in anorexia nervosa: lessons from a 21-year follow-up study. \u003cem\u003eLancet\u003c/em\u003e \u003cstrong\u003e355\u003c/strong\u003e, 721-722, doi:10.1016/S0140-6736(99)05363-5 (2000).\u003c/li\u003e\n\u003cli\u003eBulik, C. M.\u003cem\u003e et al.\u003c/em\u003e Genetics and neurobiology of eating disorders. \u003cem\u003eNat Neurosci\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 543-554, doi:10.1038/s41593-022-01071-z (2022).\u003c/li\u003e\n\u003cli\u003eWatson, H. J.\u003cem\u003e et al.\u003c/em\u003e Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. \u003cem\u003eNat Genet\u003c/em\u003e \u003cstrong\u003e51\u003c/strong\u003e, 1207-1214, doi:10.1038/s41588-019-0439-2 (2019).\u003c/li\u003e\n\u003cli\u003eFriedman, J. M. Leptin and the endocrine control of energy balance. \u003cem\u003eNat Metab\u003c/em\u003e \u003cstrong\u003e1\u003c/strong\u003e, 754-764, doi:10.1038/s42255-019-0095-y (2019).\u003c/li\u003e\n\u003cli\u003eHinney, A., Volckmar, A. L. \u0026amp; Antel, J. Genes and the hypothalamic control of metabolism in humans. \u003cem\u003eBest Pract Res Clin Endocrinol Metab\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 635-647, doi:10.1016/j.beem.2014.04.007 (2014).\u003c/li\u003e\n\u003cli\u003eJais, A. \u0026amp; Bruning, J. C. Hypothalamic inflammation in obesity and metabolic disease. \u003cem\u003eJ Clin Invest\u003c/em\u003e \u003cstrong\u003e127\u003c/strong\u003e, 24-32, doi:10.1172/JCI88878 (2017).\u003c/li\u003e\n\u003cli\u003eHinney, A., Korner, A. \u0026amp; Fischer-Posovszky, P. The promise of new anti-obesity therapies arising from knowledge of genetic obesity traits. \u003cem\u003eNat Rev Endocrinol\u003c/em\u003e, doi:10.1038/s41574-022-00716-0 (2022).\u003c/li\u003e\n\u003cli\u003eLoos, R. J. F. \u0026amp; Yeo, G. S. H. The genetics of obesity: from discovery to biology. \u003cem\u003eNat Rev Genet\u003c/em\u003e, doi:10.1038/s41576-021-00414-z (2021).\u003c/li\u003e\n\u003cli\u003eMontague, C. T.\u003cem\u003e et al.\u003c/em\u003e Congenital leptin deficiency is associated with severe early-onset obesity in humans. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e387\u003c/strong\u003e, 903-908, doi:10.1038/43185 (1997).\u003c/li\u003e\n\u003cli\u003eGibson, W. T.\u003cem\u003e et al.\u003c/em\u003e Congenital leptin deficiency due to homozygosity for the Delta133G mutation: report of another case and evaluation of response to four years of leptin therapy. \u003cem\u003eJ Clin Endocrinol Metab\u003c/em\u003e \u003cstrong\u003e89\u003c/strong\u003e, 4821-4826, doi:10.1210/jc.2004-0376 (2004).\u003c/li\u003e\n\u003cli\u003eFatima, W.\u003cem\u003e et al.\u003c/em\u003e Leptin deficiency and leptin gene mutations in obese children from Pakistan. \u003cem\u003eInt J Pediatr Obes\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 419-427, doi:10.3109/17477166.2011.608431 (2011).\u003c/li\u003e\n\u003cli\u003eSaeed, S., Butt, T. A., Anwer, M., Arslan, M. \u0026amp; Froguel, P. High prevalence of leptin and melanocortin-4 receptor gene mutations in children with severe obesity from Pakistani consanguineous families. \u003cem\u003eMol Genet Metab\u003c/em\u003e \u003cstrong\u003e106\u003c/strong\u003e, 121-126, doi:10.1016/j.ymgme.2012.03.001 (2012).\u003c/li\u003e\n\u003cli\u003eMazen, I., El-Gammal, M., Abdel-Hamid, M. \u0026amp; Amr, K. A novel homozygous missense mutation of the leptin gene (N103K) in an obese Egyptian patient. \u003cem\u003eMol Genet Metab\u003c/em\u003e \u003cstrong\u003e97\u003c/strong\u003e, 305-308, doi:10.1016/j.ymgme.2009.04.002 (2009).\u003c/li\u003e\n\u003cli\u003eWabitsch, M.\u003cem\u003e et al.\u003c/em\u003e Severe Early-Onset Obesity Due to Bioinactive Leptin Caused by a p.N103K Mutation in the Leptin Gene. \u003cem\u003eJ Clin Endocrinol Metab\u003c/em\u003e \u003cstrong\u003e100\u003c/strong\u003e, 3227-3230, doi:10.1210/jc.2015-2263 (2015).\u003c/li\u003e\n\u003cli\u003eGeller, F.\u003cem\u003e et al.\u003c/em\u003e Melanocortin-4 receptor gene variant I103 is negatively associated with obesity. \u003cem\u003eAm J Hum Genet\u003c/em\u003e \u003cstrong\u003e74\u003c/strong\u003e, 572-581, doi:10.1086/382490 (2004).\u003c/li\u003e\n\u003cli\u003eLotta, L. A.\u003cem\u003e et al.\u003c/em\u003e Human Gain-of-Function MC4R Variants Show Signaling Bias and Protect against Obesity. \u003cem\u003eCell\u003c/em\u003e \u003cstrong\u003e177\u003c/strong\u003e, 597-607 e599, doi:10.1016/j.cell.2019.03.044 (2019).\u003c/li\u003e\n\u003cli\u003eRojo, D., McCarthy, C., Raingo, J. \u0026amp; Rubinstein, M. Mouse models for V103I and I251L gain of function variants of the human MC4R display decreased adiposity but are not protected against a hypercaloric diet. \u003cem\u003eMol Metab\u003c/em\u003e \u003cstrong\u003e42\u003c/strong\u003e, 101077, doi:10.1016/j.molmet.2020.101077 (2020).\u003c/li\u003e\n\u003cli\u003eHinney, A.\u003cem\u003e et al.\u003c/em\u003e Evidence for three genetic loci involved in both anorexia nervosa risk and variation of body mass index. \u003cem\u003eMol Psychiatry\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 321-322, doi:10.1038/mp.2016.126 (2017).\u003c/li\u003e\n\u003cli\u003eZheng, Y.\u003cem\u003e et al.\u003c/em\u003e PTBP2 - a gene with relevance for both Anorexia nervosa and body weight regulation. \u003cem\u003eTransl Psychiatry\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 241, doi:10.1038/s41398-022-02018-5 (2022).\u003c/li\u003e\n\u003cli\u003eBulik-Sullivan, B.\u003cem\u003e et al.\u003c/em\u003e An atlas of genetic correlations across human diseases and traits. \u003cem\u003eNat Genet\u003c/em\u003e \u003cstrong\u003e47\u003c/strong\u003e, 1236-1241, doi:10.1038/ng.3406 (2015).\u003c/li\u003e\n\u003cli\u003eSeitz, J.\u003cem\u003e et al.\u003c/em\u003e Leptin levels in patients with anorexia nervosa following day/inpatient treatment do not predict weight 1 year post-referral. \u003cem\u003eEur Child Adolesc Psychiatry\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 1019-1025, doi:10.1007/s00787-016-0819-4 (2016).\u003c/li\u003e\n\u003cli\u003eHaas, V.\u003cem\u003e et al.\u003c/em\u003e Leptin and body weight regulation in patients with anorexia nervosa before and during weight recovery. \u003cem\u003eAm J Clin Nutr\u003c/em\u003e \u003cstrong\u003e81\u003c/strong\u003e, 889-896, doi:10.1093/ajcn/81.4.889 (2005).\u003c/li\u003e\n\u003cli\u003eHebebrand, J.\u003cem\u003e et al.\u003c/em\u003e Leptin levels in patients with anorexia nervosa are reduced in the acute stage and elevated upon short-term weight restoration. \u003cem\u003eMol Psychiatry\u003c/em\u003e \u003cstrong\u003e2\u003c/strong\u003e, 330-334, doi:10.1038/sj.mp.4000282 (1997).\u003c/li\u003e\n\u003cli\u003eHebebrand, J.\u003cem\u003e et al.\u003c/em\u003e The role of hypoleptinemia in the psychological and behavioral adaptation to starvation: Implications for anorexia nervosa. \u003cem\u003eNeurosci Biobehav Rev\u003c/em\u003e \u003cstrong\u003e141\u003c/strong\u003e, 104807, doi:10.1016/j.neubiorev.2022.104807 (2022).\u003c/li\u003e\n\u003cli\u003ePeters, T.\u003cem\u003e et al.\u003c/em\u003e Suggestive Evidence for Causal Effect of Leptin Levels on Risk for Anorexia Nervosa: Results of a Mendelian Randomization Study. \u003cem\u003eFront Genet\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 733606, doi:10.3389/fgene.2021.733606 (2021).\u003c/li\u003e\n\u003cli\u003eMilos, G.\u003cem\u003e et al.\u003c/em\u003e Short-term metreleptin treatment of patients with anorexia nervosa: rapid on-set of beneficial cognitive, emotional, and behavioral effects. \u003cem\u003eTransl Psychiatry\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 303, doi:10.1038/s41398-020-00977-1 (2020).\u003c/li\u003e\n\u003cli\u003eAntel, J.\u003cem\u003e et al.\u003c/em\u003e Rapid amelioration of anorexia nervosa in a male adolescent during metreleptin treatment including recovery from hypogonadotropic hypogonadism. \u003cem\u003eEur Child Adolesc Psychiatry\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 1573-1579, doi:10.1007/s00787-021-01778-7 (2022).\u003c/li\u003e\n\u003cli\u003eGradl-Dietsch, G.\u003cem\u003e et al.\u003c/em\u003e Rapid Emergence of Appetite and Hunger Resulting in Weight Gain and Improvement of Eating Disorder Symptomatology during and after Short-Term Off-Label Metreleptin Treatment of a Patient with Anorexia Nervosa. \u003cem\u003eObes Facts\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 99-107, doi:10.1159/000527386 (2023).\u003c/li\u003e\n\u003cli\u003eEhrlich, S.\u003cem\u003e et al.\u003c/em\u003e Promoter specific DNA methylation and gene expression of POMC in acutely underweight and recovered patients with anorexia nervosa. \u003cem\u003eJ Psychiatr Res\u003c/em\u003e \u003cstrong\u003e44\u003c/strong\u003e, 827-833, doi:10.1016/j.jpsychires.2010.01.011 (2010).\u003c/li\u003e\n\u003cli\u003eHinney, A.\u003cem\u003e et al.\u003c/em\u003e No evidence for involvement of the leptin gene in anorexia nervosa, bulimia nervosa, underweight or early onset extreme obesity: identification of two novel mutations in the coding sequence and a novel polymorphism in the leptin gene linked upstream region. \u003cem\u003eMol Psychiatry\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 539-543, doi:10.1038/sj.mp.4000394 (1998).\u003c/li\u003e\n\u003cli\u003eYilmaz, Z.\u003cem\u003e et al.\u003c/em\u003e The role of leptin, melanocortin, and neurotrophin system genes on body weight in anorexia nervosa and bulimia nervosa. \u003cem\u003eJ Psychiatr Res\u003c/em\u003e \u003cstrong\u003e55\u003c/strong\u003e, 77-86, doi:10.1016/j.jpsychires.2014.04.005 (2014).\u003c/li\u003e\n\u003cli\u003ePulit, S. L.\u003cem\u003e et al.\u003c/em\u003e Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. \u003cem\u003eHum Mol Genet\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 166-174, doi:10.1093/hmg/ddy327 (2019).\u003c/li\u003e\n\u003cli\u003eHinney, A.\u003cem\u003e et al.\u003c/em\u003e Several mutations in the melanocortin-4 receptor gene including a nonsense and a frameshift mutation associated with dominantly inherited obesity in humans. \u003cem\u003eJ Clin Endocrinol Metab\u003c/em\u003e \u003cstrong\u003e84\u003c/strong\u003e, 1483-1486, doi:10.1210/jcem.84.4.5728 (1999).\u003c/li\u003e\n\u003cli\u003eSteinhaus, R.\u003cem\u003e et al.\u003c/em\u003e MutationTaster2021. \u003cem\u003eNucleic Acids Res\u003c/em\u003e \u003cstrong\u003e49\u003c/strong\u003e, W446-W451, doi:10.1093/nar/gkab266 (2021).\u003c/li\u003e\n\u003cli\u003eBendl, J.\u003cem\u003e et al.\u003c/em\u003e PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions. \u003cem\u003ePLoS Comput Biol\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, e1004962, doi:10.1371/journal.pcbi.1004962 (2016).\u003c/li\u003e\n\u003cli\u003eYaghootkar, H.\u003cem\u003e et al.\u003c/em\u003e Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity. \u003cem\u003eDiabetes\u003c/em\u003e \u003cstrong\u003e69\u003c/strong\u003e, 2806-2818, doi:10.2337/db20-0070 (2020).\u003c/li\u003e\n\u003cli\u003eFriedlander, Y.\u003cem\u003e et al.\u003c/em\u003e Candidate molecular pathway genes related to appetite regulatory neural network, adipocyte homeostasis and obesity: results from the CARDIA Study. \u003cem\u003eAnn Hum Genet\u003c/em\u003e \u003cstrong\u003e74\u003c/strong\u003e, 387-398, doi:10.1111/j.1469-1809.2010.00596.x (2010).\u003c/li\u003e\n\u003cli\u003eStutzmann, F.\u003cem\u003e et al.\u003c/em\u003e Non-synonymous polymorphisms in melanocortin-4 receptor protect against obesity: the two facets of a Janus obesity gene. \u003cem\u003eHum Mol Genet\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 1837-1844, doi:10.1093/hmg/ddm132 (2007).\u003c/li\u003e\n\u003cli\u003ePaisdzior, S.\u003cem\u003e et al.\u003c/em\u003e Differential Signaling Profiles of MC4R Mutations with Three Different Ligands. \u003cem\u003eInt J Mol Sci\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, doi:10.3390/ijms21041224 (2020).\u003c/li\u003e\n\u003cli\u003eBrouwers, B.\u003cem\u003e et al.\u003c/em\u003e Human MC4R variants affect endocytosis, trafficking and dimerization revealing multiple cellular mechanisms involved in weight regulation. \u003cem\u003eCell Rep\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, 108862, doi:10.1016/j.celrep.2021.108862 (2021).\u003c/li\u003e\n\u003cli\u003eHinney, A.\u003cem\u003e et al.\u003c/em\u003e Melanocortin-4 receptor gene: case-control study and transmission disequilibrium test confirm that functionally relevant mutations are compatible with a major gene effect for extreme obesity. \u003cem\u003eJ Clin Endocrinol Metab\u003c/em\u003e \u003cstrong\u003e88\u003c/strong\u003e, 4258-4267, doi:10.1210/jc.2003-030233 (2003).\u003c/li\u003e\n\u003cli\u003eGu, W.\u003cem\u003e et al.\u003c/em\u003e Identification and functional analysis of novel human melanocortin-4 receptor variants. \u003cem\u003eDiabetes\u003c/em\u003e \u003cstrong\u003e48\u003c/strong\u003e, 635-639, doi:10.2337/diabetes.48.3.635 (1999).\u003c/li\u003e\n\u003cli\u003eHo, G. \u0026amp; MacKenzie, R. G. Functional characterization of mutations in melanocortin-4 receptor associated with human obesity. \u003cem\u003eJ Biol Chem\u003c/em\u003e \u003cstrong\u003e274\u003c/strong\u003e, 35816-35822, doi:10.1074/jbc.274.50.35816 (1999).\u003c/li\u003e\n\u003cli\u003eThearle, M. S.\u003cem\u003e et al.\u003c/em\u003e Greater impact of melanocortin-4 receptor deficiency on rates of growth and risk of type 2 diabetes during childhood compared with adulthood in Pima Indians. \u003cem\u003eDiabetes\u003c/em\u003e \u003cstrong\u003e61\u003c/strong\u003e, 250-257, doi:10.2337/db11-0708 (2012).\u003c/li\u003e\n\u003cli\u003eMelchior, C.\u003cem\u003e et al.\u003c/em\u003e Clinical and functional relevance of melanocortin-4 receptor variants in obese German children. \u003cem\u003eHorm Res Paediatr\u003c/em\u003e \u003cstrong\u003e78\u003c/strong\u003e, 237-246, doi:10.1159/000343816 (2012).\u003c/li\u003e\n\u003cli\u003eRovite, V.\u003cem\u003e et al.\u003c/em\u003e The role of common and rare MC4R variants and FTO polymorphisms in extreme form of obesity. \u003cem\u003eMol Biol Rep\u003c/em\u003e \u003cstrong\u003e41\u003c/strong\u003e, 1491-1500, doi:10.1007/s11033-013-2994-4 (2014).\u003c/li\u003e\n\u003cli\u003eNijenhuis, W. A., Garner, K. M., van Rozen, R. J. \u0026amp; Adan, R. A. Poor cell surface expression of human melanocortin-4 receptor mutations associated with obesity. \u003cem\u003eJ Biol Chem\u003c/em\u003e \u003cstrong\u003e278\u003c/strong\u003e, 22939-22945, doi:10.1074/jbc.M211326200 (2003).\u003c/li\u003e\n\u003cli\u003eXiang, Z.\u003cem\u003e et al.\u003c/em\u003e Pharmacological characterization of 40 human melanocortin-4 receptor polymorphisms with the endogenous proopiomelanocortin-derived agonists and the agouti-related protein (AGRP) antagonist. \u003cem\u003eBiochemistry\u003c/em\u003e \u003cstrong\u003e45\u003c/strong\u003e, 7277-7288, doi:10.1021/bi0600300 (2006).\u003c/li\u003e\n\u003cli\u003eValli-Jaakola, K.\u003cem\u003e et al.\u003c/em\u003e Identification and characterization of melanocortin-4 receptor gene mutations in morbidly obese finnish children and adults. \u003cem\u003eJ Clin Endocrinol Metab\u003c/em\u003e \u003cstrong\u003e89\u003c/strong\u003e, 940-945, doi:10.1210/jc.2003-031182 (2004).\u003c/li\u003e\n\u003cli\u003eFischer-Posovszky, P.\u003cem\u003e et al.\u003c/em\u003e A new missense mutation in the leptin gene causes mild obesity and hypogonadism without affecting T cell responsiveness. \u003cem\u003eJ Clin Endocrinol Metab\u003c/em\u003e \u003cstrong\u003e95\u003c/strong\u003e, 2836-2840, doi:10.1210/jc.2009-2466 (2010).\u003c/li\u003e\n\u003cli\u003eFarooqi, I. S.\u003cem\u003e et al.\u003c/em\u003e Clinical spectrum of obesity and mutations in the melanocortin 4 receptor gene. \u003cem\u003eN Engl J Med\u003c/em\u003e \u003cstrong\u003e348\u003c/strong\u003e, 1085-1095, doi:10.1056/NEJMoa022050 (2003).\u003c/li\u003e\n\u003cli\u003eSaeed, S.\u003cem\u003e et al.\u003c/em\u003e Genetic variants in LEP, LEPR, and MC4R explain 30% of severe obesity in children from a consanguineous population. \u003cem\u003eObesity (Silver Spring)\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, 1687-1695, doi:10.1002/oby.21142 (2015).\u003c/li\u003e\n\u003cli\u003eMurray, P. G.\u003cem\u003e et al.\u003c/em\u003e Reduced appetite and body mass index with delayed puberty in a mother and son: association with a rare novel sequence variant in the leptin gene. \u003cem\u003eEur J Endocrinol\u003c/em\u003e \u003cstrong\u003e164\u003c/strong\u003e, 521-527, doi:10.1530/EJE-10-0656 (2011).\u003c/li\u003e\n\u003cli\u003eDubern, B.\u003cem\u003e et al.\u003c/em\u003e Mutational analysis of melanocortin-4 receptor, agouti-related protein, and alpha-melanocyte-stimulating hormone genes in severely obese children. \u003cem\u003eJ Pediatr\u003c/em\u003e \u003cstrong\u003e139\u003c/strong\u003e, 204-209, doi:10.1067/mpd.2001.116284 (2001).\u003c/li\u003e\n\u003cli\u003eHeid, I. M.\u003cem\u003e et al.\u003c/em\u003e Association of the 103I MC4R allele with decreased body mass in 7937 participants of two population based surveys. \u003cem\u003eJ Med Genet\u003c/em\u003e \u003cstrong\u003e42\u003c/strong\u003e, e21, doi:10.1136/jmg.2004.027011 (2005).\u003c/li\u003e\n\u003cli\u003eHebebrand, J., Muller, T. D., Holtkamp, K. \u0026amp; Herpertz-Dahlmann, B. The role of leptin in anorexia nervosa: clinical implications. \u003cem\u003eMol Psychiatry\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 23-35, doi:10.1038/sj.mp.4001909 (2007).\u003c/li\u003e\n\u003cli\u003eWabitsch, M.\u003cem\u003e et al.\u003c/em\u003e Biologically inactive leptin and early-onset extreme obesity. \u003cem\u003eN Engl J Med\u003c/em\u003e \u003cstrong\u003e372\u003c/strong\u003e, 48-54, doi:10.1056/NEJMoa1406653 (2015).\u003c/li\u003e\n\u003cli\u003eHebebrand, J.\u003cem\u003e et al.\u003c/em\u003e Plasma concentrations of obese protein in anorexia nervosa. \u003cem\u003eLancet\u003c/em\u003e \u003cstrong\u003e346\u003c/strong\u003e, 1624-1625, doi:10.1016/s0140-6736(95)91955-4 (1995).\u003c/li\u003e\n\u003cli\u003eFan, Z. C. \u0026amp; Tao, Y. X. Functional characterization and pharmacological rescue of melanocortin-4 receptor mutations identified from obese patients. \u003cem\u003eJ Cell Mol Med\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 3268-3282, doi:10.1111/j.1582-4934.2009.00726.x (2009).\u003c/li\u003e\n\u003cli\u003eHebebrand, J.\u003cem\u003e et al.\u003c/em\u003e Genetic predisposition to obesity in bulimia nervosa: a mutation screen of the melanocortin-4 receptor gene. \u003cem\u003eMol Psychiatry\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 647-651, doi:10.1038/sj.mp.4001053 (2002).\u003c/li\u003e\n\u003cli\u003eHunt, S. C.\u003cem\u003e et al.\u003c/em\u003e Association of the FTO gene with BMI. \u003cem\u003eObesity (Silver Spring)\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 902-904, doi:10.1038/oby.2007.126 (2008).\u003c/li\u003e\n\u003cli\u003eHotta, K.\u003cem\u003e et al.\u003c/em\u003e Variations in the FTO gene are associated with severe obesity in the Japanese. \u003cem\u003eJ Hum Genet\u003c/em\u003e \u003cstrong\u003e53\u003c/strong\u003e, 546-553, doi:10.1007/s10038-008-0283-1 (2008).\u003c/li\u003e\n\u003cli\u003eMuller, T. D.\u003cem\u003e et al.\u003c/em\u003e Fat mass and obesity-associated gene (FTO) in eating disorders: evidence for association of the rs9939609 obesity risk allele with bulimia nervosa and anorexia nervosa. \u003cem\u003eObes Facts\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 408-419, doi:10.1159/000340057 (2012).\u003c/li\u003e\n\u003cli\u003eGenis-Mendoza, A. D.\u003cem\u003e et al.\u003c/em\u003e Interaction of FTO rs9939609 and the native American-origin ABCA1 p.Arg230Cys with circulating leptin levels in Mexican adolescents diagnosed with eating disorders: Preliminary results. \u003cem\u003ePsychiatry Res\u003c/em\u003e \u003cstrong\u003e291\u003c/strong\u003e, 113270, doi:10.1016/j.psychres.2020.113270 (2020).\u003c/li\u003e\n\u003cli\u003eNiroula, A. \u0026amp; Vihinen, M. How good are pathogenicity predictors in detecting benign variants? \u003cem\u003ePLoS Comput Biol\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, e1006481, doi:10.1371/journal.pcbi.1006481 (2019).\u003c/li\u003e\n\u003cli\u003ePshennikova, V. G.\u003cem\u003e et al.\u003c/em\u003e Comparison of Predictive In Silico Tools on Missense Variants in GJB2, GJB6, and GJB3 Genes Associated with Autosomal Recessive Deafness 1A (DFNB1A). \u003cem\u003eScientificWorldJournal\u003c/em\u003e \u003cstrong\u003e2019\u003c/strong\u003e, 5198931, doi:10.1155/2019/5198931 (2019).\u003c/li\u003e\n\u003cli\u003eCubuk, C.\u003cem\u003e et al.\u003c/em\u003e Clinical likelihood ratios and balanced accuracy for 44 in silico tools against multiple large-scale functional assays of cancer susceptibility genes. \u003cem\u003eGenet Med\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, 2096-2104, doi:10.1038/s41436-021-01265-z (2021).\u003c/li\u003e\n\u003cli\u003eFlanagan, S. E., Patch, A. M. \u0026amp; Ellard, S. Using SIFT and PolyPhen to predict loss-of-function and gain-of-function mutations. \u003cem\u003eGenet Test Mol Biomarkers\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 533-537, doi:10.1089/gtmb.2010.0036 (2010).\u003c/li\u003e\n\u003cli\u003eCartegni, L., Wang, J., Zhu, Z., Zhang, M. Q. \u0026amp; Krainer, A. R. ESEfinder: A web resource to identify exonic splicing enhancers. \u003cem\u003eNucleic Acids Res\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 3568-3571, doi:10.1093/nar/gkg616 (2003).\u003c/li\u003e\n\u003cli\u003eTang, H. \u0026amp; Thomas, P. D. PANTHER-PSEP: predicting disease-causing genetic variants using position-specific evolutionary preservation. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 2230-2232, doi:10.1093/bioinformatics/btw222 (2016).\u003c/li\u003e\n\u003cli\u003eParthiban, V., Gromiha, M. M. \u0026amp; Schomburg, D. CUPSAT: prediction of protein stability upon point mutations. \u003cem\u003eNucleic Acids Res\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, W239-242, doi:10.1093/nar/gkl190 (2006).\u003c/li\u003e\n\u003cli\u003eSim, N. L.\u003cem\u003e et al.\u003c/em\u003e SIFT web server: predicting effects of amino acid substitutions on proteins. \u003cem\u003eNucleic Acids Res\u003c/em\u003e \u003cstrong\u003e40\u003c/strong\u003e, W452-457, doi:10.1093/nar/gks539 (2012).\u003c/li\u003e\n\u003cli\u003eZhang, F.\u003cem\u003e et al.\u003c/em\u003e Crystal structure of the obese protein leptin-E100. \u003cem\u003eNature\u003c/em\u003e \u003cstrong\u003e387\u003c/strong\u003e, 206-209, doi:10.1038/387206a0 (1997).\u003c/li\u003e\n\u003cli\u003eIsraeli, H.\u003cem\u003e et al.\u003c/em\u003e Structure reveals the activation mechanism of the MC4 receptor to initiate satiation signaling. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e372\u003c/strong\u003e, 808-814, doi:10.1126/science.abf7958 (2021).\u003c/li\u003e\n\u003cli\u003eAllot, A.\u003cem\u003e et al.\u003c/em\u003e LitVar: a semantic search engine for linking genomic variant data in PubMed and PMC. \u003cem\u003eNucleic Acids Res\u003c/em\u003e \u003cstrong\u003e46\u003c/strong\u003e, W530-W536, doi:10.1093/nar/gky355 (2018).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3850003/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3850003/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMutations leading to a reduced or loss of function in genes of the leptin-melanocortin system confer a risk for monogenic forms of obesity. Yet, gain of function variants in the melanocortin-4-receptor (\u003cem\u003eMC4R\u003c/em\u003e) gene predispose to a lower BMI. In individuals with reduced body weight, we thus expected mutations leading to an enhanced function in the respective genes, like leptin (\u003cem\u003eLEP)\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e. Therefore, we have Sanger sequenced the coding regions of \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e in 462 female patients with AN, and 445 healthy-lean controls. In total, we have observed four and eight variants in \u003cem\u003eLEP\u003c/em\u003e and \u003cem\u003eMC4R\u003c/em\u003e, respectively. Previous studies showed different functional \u003cem\u003ein vitro\u003c/em\u003e effects for the detected frameshift and non-synonymous variants: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) \u003cem\u003eLEP\u003c/em\u003e: reduced/loss of function (p.Val94Met), (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) \u003cem\u003eMC4R\u003c/em\u003e: gain of function (p.Val103Ile, p.Ile251Leu), reduced or loss of function (p.Thr112Met, p.Ser127Leu, p.Leu211\u003cem\u003efs\u003c/em\u003eX) and without functional \u003cem\u003ein vitro\u003c/em\u003e data (p.Val50Leut). In \u003cem\u003eLEP\u003c/em\u003e, the variant p.Val94Met was detected in one patient with AN. For \u003cem\u003eMC4R\u003c/em\u003e variants, one patient with AN carried the frameshift variant p.Leu211\u003cem\u003efs\u003c/em\u003eX. One patient with AN was heterozygous for two variants at the \u003cem\u003eMC4R\u003c/em\u003e (p.Val103Ile and p.Ser127Leu). All other functionally relevant variants were detected in similar frequencies in patients with AN and lean individuals.\u003c/p\u003e","manuscriptTitle":"Unexpected identification of obesity-associated mutations in LEP and MC4R genes in patients with anorexia nervosa","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-12 16:16:58","doi":"10.21203/rs.3.rs-3850003/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-01-30T05:17:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-01-22T13:52:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2b04e207-420e-41d0-ae66-1c90ce0a4eea","date":"2024-01-19T19:45:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"b7d6c059-54c1-4e91-8147-a40b475f9657","date":"2024-01-12T06:19:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-11T23:10:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-11T19:49:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-01-11T07:48:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-11T07:35:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-01-10T10:17:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"351a0ee9-6f64-4ba8-84c7-b3d39bde6b3c","owner":[],"postedDate":"January 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28100219,"name":"Biological sciences/Genetics/Genotype"},{"id":28100220,"name":"Biological sciences/Genetics/Medical genetics"},{"id":28100221,"name":"Biological sciences/Genetics/Mutation"},{"id":28100222,"name":"Biological sciences/Genetics/Sequencing"}],"tags":[],"updatedAt":"2024-03-26T01:13:45+00:00","versionOfRecord":{"articleIdentity":"rs-3850003","link":"https://doi.org/10.1038/s41598-024-57517-w","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-03-25 01:13:45","publishedOnDateReadable":"March 25th, 2024"},"versionCreatedAt":"2024-01-12 16:16:58","video":"","vorDoi":"10.1038/s41598-024-57517-w","vorDoiUrl":"https://doi.org/10.1038/s41598-024-57517-w","workflowStages":[]},"version":"v1","identity":"rs-3850003","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3850003","identity":"rs-3850003","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}