Abstract

Objective

Obesity is a serious health problem that progressively affects individuals’ lives with comorbidities, such as heart disease, stroke, and diabetes mellitus. Since its prevalence has increased, particularly in children less than five years old, its genetic and environmental causes should be determined for prevention and control of the disease. The aim of this study was to detect underlying genetic risk factors in a family with an exclusively breastfed obese infant.

Methods: A three-generation family was recruited to be evaluated for obesity. Detailed examinations along with body mass index (BMI) calculations were performed on available family members. Whole exome sequencing (WES) was performed on a 7-month-old obese infant. Bioinformatic analyses were performed on the Genomize SEQ platform with variant filtering at minor allele frequencies <1% for all normal populations. Sanger sequencing was applied in variant confirmation and family segregation.

Results: Neuro-motor developmental features were normal and genetic syndromes were excluded from the index. Early-onset severe obesity (+4.25 standard deviation score weight-for-height) was evident in index case; his father and grandmother were also obese (BMIs 38.1 kg/m² and 31.3 kg/m², respectively). WES analysis revealed deleterious variants in SH2B1, PDE11A, ADCY3, and CAPN10 genes previously associated with obesity. All variants were evaluated as novel candidates for obesity, except PDE11A, and family segregation confirmed paternal inheritance.

Conclusion: This study confirmed the paternal inheritance of all potentially deleterious obesity-related variants. The cumulative effect of individual variants might explain the obesity phenotype in this family. The infant is recommended to be followed up periodically due to increased risk for later childhood obesity.

Keywords:

Early-onset obesity, whole exome sequencing, paternal inheritance, novel variants, body mass index

What is already known on this topic?

Obesity is a complex disorder characterized by excess body fat that manifests under the influence of genetic and environmental factors. Rapid growth during infancy and early childhood has directly been related to the onset of adult obesity. Whole exome sequencing (WES) has been used for identifying novel rare variants in disease pathogenesis. Nevertheless, the mechanism underlying this complex disease is still incompletely understood.

What this study adds?

WES analysis in combination with family segregation was used in predicting the risk for later obesity of an exclusively breastfed infant, and in providing genetic counseling to the family. The paternal inheritance of all potentially deleterious novel obesity-related variants was confirmed in the family.

Introduction

Obesity is a complex disorder characterized by excess body fat that manifests through the influence of both genetic and environmental factors. Various clinical manifestations of obesity originate from diverse phenotypic expression of genetic variants (1). Polygenic/common obesity is the most prevalent type of obesity in society, which occurs because of the effect of many polymorphisms, each contributing small effects (2). There is an imbalance between energy intake and consumption, which increases adipose tissue due to a combination of genetic predisposition and environmental factors (3). However, rare abnormalities linked to a single gene may occur and are termed monogenic or Mendelian obesity. Early-onset severe obesity is the development of obesity in early life, which might occur due to disruption in genes involved in pathways affecting energy balance, appetite, and adipocyte distribution (4). Obesity increasingly affects children under the age of 5 years, highlighting the importance of the early childhood period (5). According to the World Health Organization (WHO), in 2020 nearly 39 million children under the age of 5 years were reported to be overweight or obese (6). Therefore, if protective and preventive measures are not taken, it is predicted that one-fifth of the world’s population will be obese by 2025 (7).

Rapid growth during infancy, especially in the first 4 months, and in early childhood (within the first 2 years of life) have been directly linked with the onset of adult obesity (6, 8). Physiologic alterations in this critical developmental period contribute to the risk of obesity and comorbidities observed in adulthood (9). Consequently, infants born large for gestational age, along with rapid early growth and physical inactivity have been identified as significant risk factors for obesity (10, 11, 12). Meta-analysis comprising twin, family, and adoption studies have reported that the heritability of body mass index (BMI) ranges from 40% to 70%, implicating the role of genetics (13, 14, 15). Moreover, the genetic basis has been reported to influence hyperphagia, the disruption of energy balance, and body weight regulation, which all together may lead to severe pediatric obesity (3). Hence, genetic studies involving children are important to determine the type of obesity, its diagnosis, and the risk of recurrence, as well as in providing genetic counseling (16). In this respect, genome-wide association studies (GWAS) have been used extensively to identify common, risk-conferring alleles, while whole exome sequencing (WES) was allowed the identification of novel rare variants in disease pathogenesis (17, 18). GWAS exploits mostly non-coding single nucleotide polymorphisms (SNPs) to associate their impacts on the transcriptional regulation of nearby genes through comparison of cases and controls. Since 85% of mutations are located in protein-coding regions of the genome, WES has been used for detecting deleterious rare variants in disease pathogenesis (19). Therefore, the GWAS and WES approaches complement each other in deciphering the missing heritability in complex disorders. However, in the case of obesity research, the collective efforts of these approaches have managed to explain only 2% to 6% of the genetic component of obesity in association with BMI variation (4, 20), highlighting the need for further research in varied populations.

The aim of this study was to identify novel rare variants associated with early childhood obesity in a three-generation family having an exclusively breastfed obese infant. The inheritance of obesity appeared to be paternal. Therefore, WES analysis in combination with family segregation was used in predicting the risk for later obesity of this infant, and in providing genetic counseling to this family.

Methods

Patients and Clinical Assessments

A family from Turkiye, involving an exclusively breastfed, 7-month-old, obese male infant along with his parents and grandmother, was recruited for this study. The index (HP028) was born as the first child of non-consanguineous parents and had abnormal weight gain in the early months of life. The grandmother reported a similar growth pattern for her son, with obesity starting in his early childhood and persisting throughout his life without any comorbidity. She and her deceased spouse were reported to be obese and overweight, respectively, from early childhood. The index was subjected to a detailed clinical examination comprising physical and serological evaluations. Detailed clinical data on family history was collected from the adult recruits. In children younger than 2 years of age, obesity is diagnosed if the sex specific weight for recumbent height is more than 97.7 percentile or 2 standard deviation scores (SDS) according to WHO growth standards (21).

Weight, height, and BMI SDSs of the index case were calculated according to the growth chart prepared with national standards and weight for height SDS was based on WHO growth standards (22, 23). BMI values of adult individuals were calculated by height, and weight respectively. Following WHO standards, BMI values greater than 30 kg/m² were defined as obese and marked with black color on the pedigree (Figure 1). Written informed consents were obtained from all individuals or legal representatives in accordance with Istanbul University, Istanbul Medical Faculty Clinical Research Ethics Committee (protocol no: 2020/1054, date: 01.09.2020). According to the manufacturer’s instructions, DNA was extracted using Purelink Genomic DNA Mini Kit from peripheral blood (Invitrogen, Thermo Fisher Scientific, Inc., Waltham, MA, USA). The quantity and purity of DNA samples were measured with NanoDrop ND2000 (Thermo Fisher Scientific Inc.) spectrophotometry and samples were run on agarose gel as a final quality control.

Whole Exome Sequencing and Familial Segregation

WES was performed in the index case under the service of Izmir Tinaztepe University, Faculty of Medicine, Medical Genetic Diagnostic Center (Izmir, Turkiye). Exonic DNA was captured with the Twist Comprehensive Exome kit (Twist Bioscience, South San Francisco, CA, USA), which was used in library preparation. 36.8 Mb of protein-coding regions covering >99% of RefSeq, CCDS, and GENCODE databases were targeted in this manner. Thereafter, sequencing was performed on the Illumina NextSeq 550 platform to achieve a minimum of 20X reading depth for the targeted bases.

Sequence annotations and variant filtering were conducted on the SEQ platform version 16.7 (https://seq.genomize.com; Genomize Inc., Istanbul, Turkiye), which processes FASTQ files by aligning to the GRCh37/hg19 reference genome with a Burrows-Wheeler Alignment (BWA) tool (24). Variants were selected with Freebayes, after duplicate products and realignments of indels were removed by Genomize’s proprietary algorithms (25). Variants were annotated using VEP v102 (26). All variant prioritizations were performed for minor allele frequencies (MAF) <1% in all normal populations to detect rare variants. Initially, a whole variant list was filtered to select obesity-related genes obtained from the literature (Supplementary Table 1). Secondly, intronic and synonymous variants were filtered out. The IGV_2.9.4 program was used to visualize sequence reads. MAFs were obtained from GnomAD, 1000 Genomes Project, Exome Sequencing Project, TopMED, and SEQ-specific cohorts comprising approximately 15,000 exome sequences of individuals from Turkiye with varying disorders. A set of in silico prediction tools, including FATHMM, M-CAP, CADD, SIFT4G, DANN, Polyphen-2, and Mutation Taster were used to examine the possible impact of selected variants on protein function. Human Splicing Finder (HSF Pro v3.1, Genomnis SAS Company) was used to evaluate the impact of splice region variants. The Genomic Evolutionary Rate Profiling (GERP) score was employed to estimate the evolutionary constraint in a particular position. Sanger sequencing was used to validate the variations obtained from the WES data and to perform segregation analysis. CLC Main Workbench 8.5 was used in Sanger sequence analysis against the reference sequence of the Ensembl GRCh37.p13 version. The list of primers used in Sanger sequencing are listed in Supplementary Table 2.

Results

Clinical Evaluations

Herein, we describe a family comprising a child with excess weight gain, his parents, and his grandmother (Figure 1). Currently, the BMIs of HP030 and HP031 were calculated as 38.1 kg/m² (obese class II) and 31.3 kg/m² (obese class I), respectively, and HP031 had comorbidities of type 2 diabetes mellitus (T2DM) and hyperlipidemia. Moreover, the grandfather (#101), who died at the age of 61 due to complications caused by T2DM, was reported to be overweight. In contrast, the index’s mother (HP029) was lean, whereas her sibling (#203) and her mother (#102) were both reported to be obese, and #102 was previously diagnosed with hypertension and T2DM.

The index case, HP028, was delivered at the 42^nd gestational week by C-section with no other complications. His weight was 4,060 g (1.35 SDS), and his height was 52 cm (0.7 SDS) at delivery. He gained almost 1.5 kg per month as scaled on periodic examinations. He was admitted to our clinic when he was 7 months old, when his height and weight were measured as 74.2 cm (1.64 SDS), and 13.6 kg (4.07 SDS), respectively, and that weight-for-height was 4.25 SDS. His neuro-motor development was normal, and he showed no distinct facial or body features, making the possibility of a genetic syndrome less likely. Biochemical assessments showed no abnormalities in metabolic, thyroid, adrenal, or pituitary hormones. Hepatic ultrasound reported 2 centimeters of growth of the liver at the age of four months, which was within normal limits. During the first year of life, his weight reached 17 kg (4.22 SDS). He is still under yearly follow-up.

Whole Exome Sequencing Results

Quality metrics and filtering results achieved by WES are displayed in Table 1. WES analysis revealed four heterozygous variants in genes previously associated with obesity, which are detailed in Table 2. All variants were evaluated as novel candidates for obesity, except for the one found in PDE11A, which was previously associated with obesity cases having high blood pressure (27). These candidate variants confirmed paternal inheritance in family segregation as shown in Figure 2.

Discussion

Obesity is a multifactorial disorder that is influenced by factors such as irregular energy balance, genetic predisposition, a sedentary lifestyle, and socioeconomic status (28). Obesity has become an epidemic and is increasingly observed, especially among pediatric cases, where genetic predisposition and environmental factors lead to obesity persisting into and through adulthood (6, 29). Therefore, clinical follow-up to detect postnatal accelerated growth in the first two years of life, which is recognized as a critical period for the development of childhood obesity, may be important in the prevention of obesity and its disparities in adulthood (3, 13, 30).

In this study, we focused on the possible genetic cause of excess weight gain in an obese infant, who was exclusively breastfed. Paternal inheritance was suspected according to the family history, as his father and paternal grandparents were obese from childhood. Results obtained from WES analysis of the index identified four candidate genes that might be responsible for obesity in the members of this family. Among these candidates, two of them are stop-gained, while others are missense variations, as shown in Table 2. Paternal inheritance was confirmed for all these variants through family segregation.

The Src homology 2B adaptor protein 1 (SH2B1) p.(Gly10Arg) (rs775528324) novel missense variant was found in the heterozygous state in HP028 and HP030. This gene is involved in body weight regulation as a signaling molecule downstream of the leptin receptor. Disruptions in SH2B1 were reported to cause anomalies in the digestive system and growth abnormalities, in addition to severe early-onset obesity-insulin resistance syndrome (2). Studies uncovered the causative effects of structural variants or SNPs in this gene as directly associated with increased BMI and severe early-onset obesity (17). According to in vitro functional experiments, SH2B1 has multiple isoforms expressed in a variety of cells in the body. The SH2B1b isoform is mainly expressed in the hypothalamus, where body weight is regulated, and it also interacts with the leptin signaling pathway (31). SH2B1 enhances insulin- and leptin-induced insulin receptor substrate 2 phosphorylation and growth hormone-induced cell motility (32). Despite the many causative variants in SH2B1 linked to obesity to date, the Gly10Arg variant is described for the first time herein. We suggest that this variant is one of the candidates that might be involved in the obesity phenotype in this family, with high scores gathered from in silico predictions for evolutionary conservation by GERP (4.46), and for deleteriousness by CADD (23.30) combined.

In HP028 and HP030, the p.(Arg307Ter) rs76308115 stop-gained variant was detected in the phosphodiesterase 11A (PDE11A) gene, a member of the phosphodiesterase (PDE) family of genes. It is a null variant previously associated with obesity that causes loss of function (LOF) and the variant’s pathogenicity is predicted to be very strong by in silico tools. Along with the Arg307Ter variant (MAF<0.004), eight more pathogenic null variants in this gene were reported in ClinVar. A GERP score of 5.47 indicates a high conservation pattern for the Arg307 position. PDEs mediate cyclic-AMP (cAMP) degradation to AMP in the cAMP-dependent protein kinase (PKA) signaling pathway, which is involved in the regulation of energy balance through adipogenesis and lipogenesis (33, 34). Thus, dysregulation of this pathway has been linked to obesity. Ohlsson et al. (27) previously described the role of PDE11A Arg307Ter variant in elevated blood pressure, high BMI, abdominal obesity, and the risk of ischemic stroke, in the Swedish population. Moreover, the Arg307Ter variant has been found in patients diagnosed with pigmented nodular adrenocortical disease and Cushing syndrome, in which obesity can be observed as a component (35, 36). Nevertheless, functional validation of this variant is necessary to delineate its role in obesity pathogenicity.

The Adenylate cyclase 3 (ADCY3) p.(Ser511Leu) (rs139407103) variant is a novel missense splice-site variant. The impact of this change was reported by Human Splicing Finder (HSF Pro v3.1, Genomnis SAS Company), a splice site predictor tool as a significant alteration of exonic splicing enhancer/exonic splicing silencer motifs ratio. The variant was found to be heterozygous in HP028, while being homozygous in HP030 and HP031. This gene is known to be associated with obesity and BMI Quantitative Trait Locus 19 (BMIQ19), which consists of hyperlipidemia, hyperglyceridemia, and insulin resistance. Adenylate cyclase has a crucial role in the cAMP-dependent PKA signaling pathway by facilitating the production of cAMP from ATP (37). SNPs in the ADCY3 gene are strongly associated with obesity (38) and it was shown that selective removal of Adcy3 from the hypothalamus of a mouse led to evident body fat mass gain (39). Saeed et al. (40) suggested that recessive deleterious mutations in ADCY3 caused monogenic severe obesity, using their data obtained from genetic and functional studies. It was determined that deep RNA sequencing among homozygous and heterozygous carriers of an ADCY3 splice-site variation caused severe and intermediate decrement in RNA expression levels, respectively (41). Variations causing splice site disruptions may initiate exon skipping or intron retention, which in turn might impair ADCY3 function through generating different isoforms. Therefore, the impact of the novel Ser511Leu splice-site variant on both RNA expression and novel isoform generation merits further evaluation.

The Calpain-10 (CAPN10) p.(Cys28Ter) stop-gained novel variant was confirmed in HP028, HP030 and HP031. It is a null variant with LOF effects with extremely low frequency in the gnomAD population databases (MAF=0.0000), which has not previously been reported in ClinVar. Diabetes mellitus, insulin-stimulated glucose uptake, dyslipidemia, adipose tissue disorders, and excess weight gain are known to be associated with CAPN10. Functional studies suggest that Calpain-10 is involved in the regulation of glucose homeostasis by participating in the remodeling of the cytoskeleton and catalyzing the translocation of GLUT4 (42). Polymorphisms in this gene were found to play roles in the thermogenesis and beta (3)-adrenoceptor function of obese individuals by reducing lipolytic sensitivity (43). The previously identified C-allele of SNP-44 in CAPN10 was associated with elevated BMI and obesity, especially in the Chinese population and Turkish T2DM patients (44, 45). While particular SNPs were found to regulate lipid metabolism, and lipogenesis in adipocytes, hence contributing to obesity (46), other SNPs were associated with lower BMI rates, particularly in Japanese populations (47). Prior knowledge of this gene concerning obesity along with predictions of LOF by in silico tools strongly suggests a role of this variant in the onset of obesity in this family. The results have confirmed the paternal inheritance of all potentially deleterious obesity-related variants. As the functional significance of most of these variants is not fully elucidated, it is presumed that the cumulative effect of these individual SNPs might explain the obesity phenotype observed in this family. Therefore, bearing in mind the father’s (HP030) excess weight gain starting in childhood and the paternal inheritance of obesity-related genetic variants detected in this family, genetic counseling was provided to the index (HP028). In this respect, HP028 was predicted to be at increased risk for later obesity, so he should be under regular follow-up accordingly.

Prenatal and perinatal (fetal and early postnatal) influences, such as maternal age and eating habits, the existence of maternal metabolic disorders, intrauterine malnourishment, and even maternal smoking addictions were reported to interact markedly with infant adiposity. Thus, in the intrauterine period, the presence of gestational diabetes mellitus, and insufficient intrauterine nourishment were reported to be causative factors in obesity development (5, 48, 49). However, interviews with the mother (HP029) informed us of the absence of all these pre- and perinatal risk factors. Her BMI was in normal range (BMI: 22.7 kg/m²) during and after pregnancy, and her weight gain during pregnancy was within acceptable limits. She did not manifest any metabolic disorders that appeared before, during, or after her labor, nor did she smoke. Hence, we believe that intrauterine risk factors can be excluded for this infant. In terms of postnatal influences, the infant was exclusively breastfed, the fact behind the rationale for this study focusing on delineating genetic components of obesity. However, interviews with the parents revealed that they followed a sedentary life, in which their high BMI and resistance to losing weight could probably have resulted from a combined effect of both lifestyle and the genetic variants they were found to carry.

Study Limitations

Our study is limited since it lacks functional validations, but nevertheless provides some novel, potentially obesity-related genetic variants. So, despite the limitation of small sample size due to inclusion of a single family, the power of detecting rare pathogenic variants, as a result of decreased gene pool, is important in identifying the genetic aspects of complex disorders. Therefore, by investigating a family at high-risk for obesity, we have been able to identify novel genetic variants that have the potential to be the causative variants in this family. However, these suggestions need to be validated, both functionally and by independent cohort studies, in order to assign definite roles to these variants in the pathogenesis of obesity.

Conclusion

Obesity is a complex disorder that involves both genetic and environmental risk factors. Herein, we described three generations of a family having an obese infant, who was exclusively breastfed, suggesting a genetic background for his phenotype and hence the rationale for the study. The clinical and genetic analyses revealed a paternal inheritance of obesity-related variants that may have influenced the condition in this baby. However, the family was advised about the need to exercise regularly in addition to adapting a healthy and balanced diet, due to the complex nature of obesity. Moreover, with the identified genetic risks factors, the infant will undergo regular follow-up assessments to prevent potential health issues. This proactive approach aims to enable early interventions and personalized care strategies, thereby promoting the child’s long-term well-being and development.

Ethics

Ethics Committee Approval: This study was approved by Istanbul University, Istanbul Medical Faculty Clinical Research Ethics Committee (protocol no: 2020/1054, date: 01.09.2020).

Informed Consent: Written and oral informed consents were taken from the family members or legal representatives.

Presented in: The findings of this study were presented as a poster at the European Society of Human Genetics Conference 2023.

Authorship Contributions

Surgical and Medical Practices: Ayşe Pınar Öztürk, Şükran Poyrazoğlu, Concept: Hazal Banu Olgun Çelebioğlu, Şükran Poyrazoğlu, Feyza Nur Tuncer, Design: Hazal Banu Olgun Çelebioğlu, Şükran Poyrazoğlu, Feyza Nur Tuncer, Data Collection or Processing: Hazal Banu Olgun Çelebioğlu, Ayşe Pınar Öztürk, Feyza Nur Tuncer, Analysis or Interpretation: Hazal Banu Olgun Çelebioğlu, Feyza Nur Tuncer, Literature Search: Hazal Banu Olgun Çelebioğlu, Writing: Hazal Banu Olgun Çelebioğlu, Şükran Poyrazoğlu, Feyza Nur Tuncer.

Conflict of interest: None declared.

Financial Disclosure: This study was supported by a grant from the Scientific Research Projects Coordination Unit of Istanbul University (TDK-2020-37103).

References

Huvenne H, Dubern B, Clément K, Poitou C. Rare Genetic Forms of Obesity: Clinical Approach and Current Treatments in 2016. Obes Facts. 2016;9:158-173. Epub 2016 Jun 1

Loos RJF, Yeo GSH. The genetics of obesity: from discovery to biology. Nat Rev Genet. 2022;23:120-133. Epub 2021 Sep 23

Littleton SH, Berkowitz RI, Grant SFA. Genetic Determinants of Childhood Obesity. Mol Diagn Ther. 2020;24:653-663. Epub 2020 Oct 1

Saeed S, Arslan M, Froguel P. Genetics of Obesity in Consanguineous Populations: Toward Precision Medicine and the Discovery of Novel Obesity Genes. Obesity (Silver Spring). 2018;26:474-484.

Brisbois TD, Farmer AP, McCargar LJ. Early markers of adult obesity: a review. Obes Rev. 2012;13:347-367. Epub 2011 Dec 16

Organization. WHO. Obesity and overweight. Last Accessed Date: 10.09.2020. Available from: https://www.who.int/ news-room/fact- sheets/detail/obesity-and-overweight

NCD Risk Factor Collaboration (NCD-RisC). Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants. Lancet. 2016;387:1377-1396.

Ong KK, Ahmed ML, Emmett PM, Preece MA, Dunger DB. Association between postnatal catch-up growth and obesity in childhood: prospective cohort study. BMJ. 2000;320:967-971.

Dietz WH. “Adiposity rebound”: reality or epiphenomenon? Lancet. 2000;356:2027-2028.

Woo Baidal JA, Locks LM, Cheng ER, Blake-Lamb TL, Perkins ME, Taveras EM. Risk Factors for Childhood Obesity in the First 1,000 Days: A Systematic Review. Am J Prev Med. 2016;50:761-779. Epub 2016 Feb 22

Moschonis G, Grammatikaki E, Manios Y. Perinatal predictors of overweight at infancy and preschool childhood: the GENESIS study. Int J Obes (Lond). 2008;32:39-47. Epub 2007 Dec 4

Lanigan J. Prevention of overweight and obesity in early life. Proc Nutr Soc. 2018;77:247-256. Epub 2018 May 29

Stagi S, Bianconi M, Sammarco MA, Artuso R, Giglio S, de Martino M. New Thoughts on Pediatric Genetic Obesity: Pathogenesis, Clinical Characteristics and Treatment Approach. Adiposity Omics and Molecular Understanding. InTech; 2017.

Elks CE, den Hoed M, Zhao JH, Sharp SJ, Wareham NJ, Loos RJ, Ong KK. Variability in the heritability of body mass index: a systematic review and meta-regression. Front Endocrinol (Lausanne). 2012;3:29.

Bouchard C. Genetics of Obesity: What We Have Learned Over Decades of Research. Obesity (Silver Spring). 2021;29:802-820.

Paolacci S, Pompucci G, Paolini B, Del Ciondolo I, Miggiano GAD, Aquilanti B, Scaramuzza A, Velluti V, Matera G, Gagliardi L, Bertelli M. Mendelian non-syndromic obesity. Acta Biomed. 2019;90:87-89.

Yengo L, Sidorenko J, Kemper KE, Zheng Z, Wood AR, Weedon MN, Frayling TM, Hirschhorn J, Yang J, Visscher PM; GIANT Consortium. Meta-analysis of genome-wide association studies for height and body mass index in ~700000 individuals of European ancestry. Hum Mol Genet. 2018;27:3641-3649.

Akbari P, Gilani A, Sosina O, Kosmicki JA, Khrimian L, Fang YY, Persaud T, Garcia V, Sun D, Li A, Mbatchou J, Locke AE, Benner C, Verweij N, Lin N, Hossain S, Agostinucci K, Pascale JV, Dirice E, Dunn M; Regeneron Genetics Center; DiscovEHR Collaboration; Kraus WE, Shah SH, Chen YI, Rotter JI, Rader DJ, Melander O, Still CD, Mirshahi T, Carey DJ, Berumen-Campos J, Kuri-Morales P, Alegre-Díaz J, Torres JM, Emberson JR, Collins R, Balasubramanian S, Hawes A, Jones M, Zambrowicz B, Murphy AJ, Paulding C, Coppola G, Overton JD, Reid JG, Shuldiner AR, Cantor M, Kang HM, Abecasis GR, Karalis K, Economides AN, Marchini J, Yancopoulos GD, Sleeman MW, Altarejos J, Della Gatta G, Tapia-Conyer R, Schwartzman ML, Baras A, Ferreira MAR, Lotta LA. Sequencing of 640,000 exomes identifies GPR75 variants associated with protection from obesity. Science. 2021;373:eabf8683.

Kina BG, Topbas Selcuki NF, Bahat PY, Usta T, Aydin S, Rahmioglu N, Tuncer FN, Oral E. Whole exome sequencing reveals novel candidate variants for endometriosis utilizing multiple affected members in a single family. Mol Genet Genomic Med. 2024;12:e2312. Epub 2023 Nov 27

Vourdoumpa A, Paltoglou G, Charmandari E. The Genetic Basis of Childhood Obesity: A Systematic Review. Nutrients. 2023;15:1416.

Grummer-Strawn LM, Reinold C, Krebs NF; Centers for Disease Control and Prevention (CDC). Use of World Health Organization and CDC growth charts for children aged 0-59 months in the United States. MMWR Recomm Rep. 2010;59:1-15. Erratum in: MMWR Recomm Rep. 2010;59:1184.

Neyzi O, Bundak R, Gökçay G, Günöz H, Furman A, Darendeliler F, Baş F. Reference Values for Weight, Height, Head Circumference, and Body Mass Index in Turkish Children. J Clin Res Pediatr Endocrinol. 2015;7:280-293.

Kurtoğlu S, Hatipoğlu N, Mazıcıoğlu MM, Akın MA, Çoban D, Gökoğlu S, Baştuğ O. Body weight, length and head circumference at birth in a cohort of Turkish newborns. J Clin Res Pediatr Endocrinol. 2012;4:132-139. Epub 2012 May 4

Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25:1754-1760. Epub 2009 May 18

Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. arXiv. 2016;1207.

McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, Flicek P, Cunningham F. The Ensembl Variant Effect Predictor. Genome Biol. 2016;17:122.

Ohlsson T, Lindgren A, Engström G, Jern C, Melander O. A stop-codon of the phosphodiesterase 11A gene is associated with elevated blood pressure and measures of obesity. J Hypertens. 2016;34:445-451.

Lin X, Li H. Obesity: Epidemiology, Pathophysiology, and Therapeutics. Front Endocrinol (Lausanne). 2021;12:706978.

Kelly AS. Current and future pharmacotherapies for obesity in children and adolescents. Nat Rev Endocrinol. 2023;19:534-541. Epub 2023 Jun 19

Díaz-Rodríguez M, Pérez-Muñoz C, Lendínez-de la Cruz JM, Fernández-Gutiérrez M, Bas-Sarmiento P, Ferriz-Mas BC. Effectiveness of a Multifactorial Intervention in the First 1000 Days of Life to Prevent Obesity and Overweight in Childhood: Study Protocol. Int J Environ Res Public Health. 2020;17:2239.

Ren D, Zhou Y, Morris D, Li M, Li Z, Rui L. Neuronal SH2B1 is essential for controlling energy and glucose homeostasis. J Clin Invest. 2007;117:397-406. Epub 2007 Jan 18

Giuranna J, Volckmar AL, Heinen A, Peters T, Schmidt B, Spieker A, Straub H, Grallert H, Müller TD, Antel J, Haußmann U, Klafki H, Rui L, Hebebrand J, Hinney A. The Effect of SH2B1 Variants on Expression of Leptin- and Insulin-Induced Pathways in Murine Hypothalamus. Obes Facts. 2018;11:93-108. Epub 2018 Apr 10 Erratum in: Obes Facts. 2018;11:176-180.

London E, Bloyd M, Stratakis CA. PKA functions in metabolism and resistance to obesity: lessons from mouse and human studies. J Endocrinol. 2020;246:51-64.

Tong T, Shen Y, Lee HW, Yu R, Park T. Adenylyl cyclase 3 haploinsufficiency confers susceptibility to diet-induced obesity and insulin resistance in mice. Sci Rep. 2016;6:34179.

Horvath A, Boikos S, Giatzakis C, Robinson-White A, Groussin L, Griffin KJ, Stein E, Levine E, Delimpasi G, Hsiao HP, Keil M, Heyerdahl S, Matyakhina L, Libè R, Fratticci A, Kirschner LS, Cramer K, Gaillard RC, Bertagna X, Carney JA, Bertherat J, Bossis I, Stratakis CA. A genome-wide scan identifies mutations in the gene encoding phosphodiesterase 11A4 (PDE11A) in individuals with adrenocortical hyperplasia. Nat Genet. 2006;38:794-800. Epub 2006 Jun 11

Libé R, Horvath A, Vezzosi D, Fratticci A, Coste J, Perlemoine K, Ragazzon B, Guillaud-Bataille M, Groussin L, Clauser E, Raffin-Sanson ML, Siegel J, Moran J, Drori-Herishanu L, Faucz FR, Lodish M, Nesterova M, Bertagna X, Bertherat J, Stratakis CA. Frequent phosphodiesterase 11A gene (PDE11A) defects in patients with Carney complex (CNC) caused by PRKAR1A mutations: PDE11A may contribute to adrenal and testicular tumors in CNC as a modifier of the phenotype. J Clin Endocrinol Metab. 2011;96:208-214. Epub 2010 Nov 3

Wu L, Shen C, Seed Ahmed M, Östenson CG, Gu HF. Adenylate cyclase 3: a new target for anti-obesity drug development. Obes Rev. 2016;17:907-914. Epub 2016 Jun 3

Tian Y, Peng B, Fu X. New ADCY3 Variants Dance in Obesity Etiology. Trends Endocrinol Metab. 2018;29:361-363. Epub 2018 Feb 14

Cao H, Chen X, Yang Y, Storm DR. Disruption of type 3 adenylyl cyclase expression in the hypothalamus leads to obesity. Integr Obes Diabetes. 2016;2:225-228. Epub 2016 May 13

Saeed S, Bonnefond A, Tamanini F, Mirza MU, Manzoor J, Janjua QM, Din SM, Gaitan J, Milochau A, Durand E, Vaillant E, Haseeb A, De Graeve F, Rabearivelo I, Sand O, Queniat G, Boutry R, Schott DA, Ayesha H, Ali M, Khan WI, Butt TA, Rinne T, Stumpel C, Abderrahmani A, Lang J, Arslan M, Froguel P. Loss-of-function mutations in ADCY3 cause monogenic severe obesity. Nat Genet. 2018;50:175-179. Epub 2018 Jan 8

Grarup N, Moltke I, Andersen MK, Dalby M, Vitting-Seerup K, Kern T, Mahendran Y, Jørsboe E, Larsen CVL, Dahl-Petersen IK, Gilly A, Suveges D, Dedoussis G, Zeggini E, Pedersen O, Andersson R, Bjerregaard P, Jørgensen ME, Albrechtsen A, Hansen T. Loss-of-function variants in ADCY3 increase risk of obesity and type 2 diabetes. Nat Genet. 2018;50:172-174. Epub 2018 Jan 8

Turner MD, Cassell PG, Hitman GA. Calpain-10: from genome search to function. Diabetes Metab Res Rev. 2005;21:505-514.

Hoffstedt J, Näslund E, Arner P. Calpain-10 gene polymorphism is associated with reduced beta(3)-adrenoceptor function in human fat cells. J Clin Endocrinol Metab. 2002;87:3362-3367.

Chen SF, Lu XF, Yan WL, Huang JF, Gu DF. Variations in the calpain-10 gene are associated with the risk of type 2 diabetes and hypertension in northern Han Chinese population. Chin Med J (Engl). 2007;120:2218-2223.

Demirci H, Yurtcu E, Ergun MA, Yazici AC, Karasu C, Yetkin I. Calpain 10 SNP-44 gene polymorphism affects susceptibility to type 2 diabetes mellitus and diabetic-related conditions. Genet Test. 2008;12:305-309.

Pánico P, Salazar AM, Burns AL, Ostrosky-Wegman P. Role of calpain-10 in the development of diabetes mellitus and its complications. Arch Med Res. 2014;45:103-115. Epub 2014 Feb 4

Shima Y, Nakanishi K, Odawara M, Kobayashi T, Ohta H. Association of the SNP-19 genotype 22 in the calpain-10 gene with elevated body mass index and hemoglobin A1c levels in Japanese. Clin Chim Acta. 2003;336:89-96.

Larqué E, Labayen I, Flodmark CE, Lissau I, Czernin S, Moreno LA, Pietrobelli A, Widhalm K. From conception to infancy - early risk factors for childhood obesity. Nat Rev Endocrinol. 2019;15:456-478. Epub 2019 Jul 3

Oken E, Gillman MW. Fetal origins of obesity. Obes Res. 2003;11:496-506.

Whole Exome Sequencing Revealed Paternal Inheritance of Obesity-related Genetic Variants in a Family with an Exclusively Breastfed Infant