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Povišana raven nalaganja maščob pri debelosti ima večfaktorsko etiologijo. V zelo redkih primerih je rezultat ene same mutacije z velikim učinkom (monogena oblika) ali pa je posledica številnih genetskih različic z majhnimi učinki, vpliv katerih se sešteva v poligensko obliko debelosti. Slednjo obliko je težje diagnosticirati, ker je kvantitativni in kvalitativni doprinos različnih genov k bolezni v veliki meri še nepoznan, znano je le, da so učinki zelo majhni. Genska družina HIF je primer takšne skupine metabolno pomembnih genov, ki so aktivni tudi v maščobnem tkivu debelih posameznikov. Povezali so jih s kroničnimi vnetji, ki so eden izmed vzrokov za razvoj sladkorne bolezni tipa 2 in drugih metabolnih bolezni. Njihova morebitna vloga pri razvoju poligenske debelosti je še nepoznana. Namen te raziskave je bil odkriti razlike v regulatornih regijah genske družine Hif (Hif1, Epas1 in Hif3a) med selekcioniranima skupinama laboratorijskih miši. Po 60 generacijah selekcije med njima obstaja več kot petkratna razlika v masi telesnega maščevja. Odkrite različice smo umestili v referenčno zaporedje iz zbirke Ensembl in SwissRegulon, prikazali pa smo jih v programu GenomeBrowse. Rezultati bioinformacijske analize so pokazali, da je med linijama znotraj teh genov 418 razlik v zaporedju, večina v genu Hif1a debele linije. Od vseh odkritih različic se jih 24 nahaja v poznanih regulatornih zaporedjih. Glede na lokacijo različic v genih in vrednost GERP smo iz širokega nabora podatkov izbrali 28 različic nukleotidnega zaporedja, ki predstavljajo obetavne kandidate za nadaljnje raziskovanje in oceno njihove morebitne kavzalne vloge pri razvoju debelosti. The elevated rate of fat accumulation in obese individuals has a multifactorial etiology. In extremely rare cases, it can develop as a result of a single mutation with large effect (monogenic form), or as a combined effect of a multitude of less impactful genetic variants representing a polygenic form of obesity. This form is harder to diagnose since the effect size of different genes is very small and the type of action is still largely unknown. HIF gene family is an example of metabolically relevant genes, which are also active in the fat tissue of obese individuals. They have been linked with chronic inflammation, which is one of the causes ort he development of type 2 diabetes and other metabolic diseases. Their possible role in the onset of polygenic obesity has not yet been recognized. The goal of this study was to find differences in regulatory regions of the Hif gene family (Hif1, Epas1 in Hif3a) between two groups of selectively breed laboratory mice. After 60 generations of selection there is more than a five-fold difference in body fat percentage between them. All discovered variations were positioned in the reference sequence from the Ensembl and SwissRegulon databases, and visualized in the GenomeBrowse program. Results showed that there are 418 sequence differences between the lines, most of which are located in the Hif1a gene of the fat line. Out of all detected variants, 24 of them are located within regulatory regions. We have selected 28 of the most promising sequence variants based on their location and GERP value, that represent viable candidates for future studies aimed at identifying their causal role in the obesity development.

Background. Eating disorders, formed in childhood, cause a high level of obesity, including its complicated course, throughout the world and require personalized preventive interventions. The purpose was to study the associations of the type of eating behavior with the phenotypes of obesity in children aged 6–16 years old. Materials and methods. One-hundred and nine 109 children with polygenic obesity aged 6–16 years were examined. The first group (n = 40) included patients with the phenotype of metabolically unhealthy obesity, the second group (n = 69) was formed by patients with the phenotype of metabolically healthy obesity. The recommendations of the expert group of the National Heart, Lung, and Blood Institute (NHLBI) were used as criteria for metabolically unhealthy obesity in children and adolescents. The Dutch DEBQ questionnaire was used to assess the type of eating behavior. The emotional type of eating behavior was determined when evaluated on the corresponding DEBQ scale more than 1.8 points, the external type — when assessed on the corresponding DEBQ scale more than 2.7 points and the restrictive type — when assessed on the corresponding DEBQ scale more than 2.4 points. Results. External (3.48 ± 0.16 points; 52.50 ± 5.09 %) and emotiogenic (2.92 ± 0.24 points; 34.20 ± 5.92 %) types of eating disorders were equally often diagnosed in children suffering from metabolically unhealthy obesity with a moderate degree of deviation above normal, p > 0.05. The restrictive type of eating behavior was observed in the phenotype of metabolically healthy obesity (2.52 ± 0.20 points, with a very low degree of deviation above the norm of 9.40 ± 2.92 %). Conclusions. Eating behaviors in children aged 6–16 years are associated with obesity phenotypes and require personalized nutritional modification. The external type of eating behavior has the greatest correlation with the formation of the phenotype of metabolically unhealthy obesity, while the phenotype of metabolically healthy obesity correlates with the restrictive type of eating behavior., Актуальность. Нарушения пищевого поведения, формирующиеся в детском возрасте, обусловливают высокий уровень распространения ожирения, в том числе и ­осложненного его течения, во всем мире и нуждаются в персонифицированных профилактических вмешательствах. Цель: изучить ассоциации типа нарушения пищевого поведения с фенотипами ожирения у детей в возрасте 6–16 лет. Материалы и методы. Обследованы 109 детей с полигенным ожирением в возрасте 6–16 лет. В первую группу (n = 40) были включены пациенты с фенотипом метаболически нездорового ожирения, вторую группу (n = 69) сформировали больные с фенотипом метаболически здорового ожирения. В качестве критериев метаболически нездорового ожирения у детей и подростков были использованы рекомендации экспертной группы Национального института здоровья сердца, легких и крови США (National Heart, Lung, and Blood Institute). Для оценки типа пищевого поведения использовался голландский опросник DEBQ. Эмоциогенный тип пищевого поведения определялся при оценке по соответствующей шкале DEBQ более 1,8 балла, экстернальный тип — при оценке по соответствующей шкале DEBQ более 2,7 балла и ограничительный тип — при оценке по соответствующей шкале DEBQ более 2,4 балла. Результаты. Экстернальный (3,48 ± 0,16 балла; 52,50 ± 5,09 %) и эмоциогенный (2,92 ± 0,24 балла; 34,20 ± 5,92 %) типы нарушения пищевого поведения одинаково часто диагностировали у детей, страдающих метаболически нездоровым ожирением со «средней» степенью отклонения выше нормы, р > 0,05. Ограничительный тип пищевого поведения отмечался при фенотипе метаболически здорового ожирения (2,52 ± 0,20 балла, с «очень низкой» степенью отклонения выше нормы 9,40 ± 2,92 %). Выводы. Типы пищевого поведения у детей в возрасте 6–16 лет ассоциированы с фенотипами ожирения и требуют персонифицированной пищевой модификации. Наибольшую корреляцию с формированием фенотипа метаболически нездорового ожирения имеет экстернальный тип пищевого поведения, тогда как фенотип метаболически здорового ожирения коррелирует с ограничительным типом пищевого поведения., Актуальність. Порушення харчової поведінки, що формуються в дитячому віці, зумовлюють високий рівень поширення ожиріння, зокрема й ускладненого його перебігу, в усьому світі та потребують персоніфікованих профілактичних втручань. Мета: вивчити асоціації типу порушення харчової поведінки з фенотипами ожиріння у дітей віком 6–16 років. Матеріали та методи. Обстежено 109 дітей із полігенним ожирінням віком 6–16 років. До першої групи (n = 40) було включено пацієнтів з фенотипом метаболічно нездорового ожиріння, другу групу (n = 69) сформували хворі з фенотипом метаболічно здорового ожиріння. Як критерії метаболічно нездорового ожиріння у дітей та підлітків були використані рекомендації експертної групи Національного інституту здоров’я серця, легень та крові США (National Heart, Lung, and Blood Institute). Для оцінки типу харчової поведінки використовувався голландський опитувальник DEBQ. Емоціогенний тип харчової поведінки визначався при оцінці за відповідною шкалою DEBQ понад 1,8 бала, екстернальний тип — при оцінці за відповідною шкалою DEBQ понад 2,7 бала й обмежувальний тип — при оцінці за відповідною шкалою DEBQ понад 2,4 бала. Результати. Екстернальний (3,48 ± 0,16 бала; 52,50 ± 5,09 %) та емоціогенний (2,92 ± 0,24 бала; 34,20 ± 5,92 %) типи порушення харчової поведінки однаково часто діагностували у дітей, які страждають на метаболічно нездорове ожиріння із «середнім» ступенем відхилення вище від норми, р > 0,05. Обме­жувальний тип харчової поведінки відзначався при фенотипі метаболічно здорового ожиріння (2,52 ± 0,20 бала; з «дуже низьким» ступенем відхилення вище від норми 9,40 ± 2,92 %). Висновки. Типи харчової поведінки у дітей віком 6–16 років асоційовані з фенотипами ожиріння та вимагають персоніфікованої харчової модифікації. Найсильніший кореляційний зв’язок із формуванням фенотипу метаболічно нездорового ожиріння має екстернальний тип харчової поведінки, тоді як фенотип метаболічно здорового ожиріння корелює з обмежувальним типом харчової поведінки.

The prevalence of obesity has tripled over the past four decades, imposing an enormous burden on people’s health. Polygenic (or common) obesity and rare, severe, early-onset monogenic obesity are often polarized as distinct diseases. However, gene discovery studies for both forms of obesity show that they have shared genetic and biological underpinnings, pointing to a key role for the brain in the control of body weight. Genome-wide association studies (GWAS) with increasing sample sizes and advances in sequencing technology are the main drivers behind a recent flurry of new discoveries. However, it is the post-GWAS, cross-disciplinary collaborations, which combine new omics technologies and analytical approaches, that have started to facilitate translation of genetic loci into meaningful biology and new avenues for treatment. In this Review, Loos and Yeo summarize our current understanding of the genetic underpinnings of monogenic and polygenic obesity. They highlight the commonalities revealed by recent studies and discuss the implications for treatment and prediction of obesity risk.

Genetics is now known to play a substantial role in the predisposition to obesity and may contribute up to 70% risk for the disease. Over a hundred genes and gene variants related to excess weight have been discovered. Yet, genetic obesity risk does not always translate into actual obesity development, suggesting complex interactions between genetic, behavioral, and environmental influences and resulting epigenetic changes. Rare but serious forms of monogenic obesity typically appear in early childhood. Polygenic obesity is most common and demonstrates strong interplay between genes and the obesogenic environment. This review provides an overview of genetic causes of obesity, potential mechanisms of epigenetic changes, and environmental influences that should diminish obesity bias and offer hope for more effective obesity prevention and intervention strategies.

Objective - This study examined the relationship between parental obesity polygenic risk and children’s BMI throughout adolescence. Additionally, from a smaller subsample, the objective was to assess whether parental polygenic risk score (PRS) may act as a proxy for offspring PRS in studies lacking offspring genetic data. Methods - A total of 8,561 parent-offspring (age 13-19 years) trios from the Trøndelag Health Study (the HUNT Study) were included, of which, 1,286 adolescents had available genetic data. Weighted parental PRSs from 900 single-nucleotide polymorphisms robustly associated with adult BMI were constructed and applied in linear mixed-effects models. Results - A positive association between parental PRS and offspring sex- and age-adjusted BMI (iso-BMI) throughout adolescence was identified. The estimated marginal effects per standard deviation increase in parental PRS were 0.26 (95% CI: 0.18-0.33), 0.36 (95% CI: 0.29-0.43), and 0.62 kg/m2 (95% CI: 0.51-0.72) for maternal, paternal, and combined parental PRS, respectively. In subsample analyses, the magnitude of association of the parental PRS versus offspring PRS with iso-BMI in adolescents was similar. Conclusions - Parental PRS was consistently associated with offspring iso-BMI throughout adolescence. Results from subsample analyses support the use of parental PRS of obesity as a proxy for adolescent PRS in the absence of offspring genetic data.

Obesity results from the complex interplay of environmental, social, behavioral, and biological determinants. Heritability values of 40–75% have been reported for obesity. Numerous genes associated with monogenic syndromic, monogenic non-syndromic, oligogenic and polygenic obesity have been identified in the past two decades. In this article, we review nine monogenic non-syndromic/oligogenic obesity genes and their role in energy maintenance as part of the leptin-melanocortin pathway. Furthermore, we discuss the relevance of early genetic testing and the availability of established and emerging treatments for monogenic non-syndromic/oligogenic obesity cases.

Research suggests that posttraumatic stress disorder (PTSD) is associated with metabolic syndrome (MetS) and that PTSD-associated MetS is related to decreased cortical thickness. However, the role of genetic factors in these associations is unclear. This study evaluated contributions of polygenic obesity risk and PTSD to MetS and of MetS and polygenic obesity risk to cortical thickness.196 white, non-Hispanic veterans of the wars in Iraq and Afghanistan underwent clinical diagnostic interviews, physiological assessments, and genome-wide genotyping; 168 also completed magnetic resonance imaging scans. Polygenic risk scores (PRSs) for obesity were calculated from results of a prior genome-wide association study (Speliotes et al., 2010) and PTSD and MetS severity factor scores were obtained.Obesity PRS (β=0.15, p=0.009) and PTSD (β=0.17, p=0.005) predicted MetS and interacted such that the association between PTSD and MetS was stronger in individuals with greater polygenic obesity risk (β=0.13, p=0.02). Whole-brain vertex-wise analyses suggested that obesity PRS interacted with MetS to predict decreased cortical thickness in left rostral middle frontal gyrus (β=-0.40, p0.001).Results suggest that PTSD, genetic variability, and MetS are related in a transactional fashion wherein obesity genetic risk increases stress-related metabolic pathology, and compounds the ill health effects of MetS on the brain. Genetic proclivity towards MetS should be considered in PTSD patients when prescribing psychotropic medications with adverse metabolic profiles. Results are consistent with a growing literature suggestive of PTSD-related accelerated aging.

Venkatesan Radha,1 Viswanathan Mohan1,2 1Department of Molecular Genetics, Madras Diabetes Research Foundation, 2Dr. Mohan’s Diabetes Specialties Centre, WHO Collaborating Centre for Noncommunicable Diseases, Prevention and Control, IDF Centrefor Education, Gopalapuram, Chennai, India Abstract: Obesity is a heterogeneous disorder, its biological causes being complex. The escalating frequency of obesity during the past few decades is due to environmental factors such as sedentary lifestyle and overnutrition, but who becomes obese at an individual level is determined by genetic susceptibility. Understanding of the molecular cause of obesity is still in its infancy. More research is needed in the area of obesity genetics and epigenetics before formulating public health prescription as presently it would not be cost-effective. This review delineates monogenic form of obesity and the multifactorial nature of common forms of obesity, due to the interaction of genes, environment, and lifestyle. Keywords: obesity, genes, genomics, monogenic obesity, polygenic obesity

Genetics, and by extention DNA sequencing, are tools that have modified the understanding of the mechanisms involved in genetic diseases, like obesity. Today’s technology has allowed us to rapidly find if a patient carries a genetic event that may explain his/her pathology. One of the most used technology for diagnostic is exome sequencing, or WES, which enables an excellent detection of point mutations in coding regions of the genome. However other events, such as copy number variations, or CNV, can also explain some pathologies, like a severe form of obesity due to CNV in the chr16p11.2 region. Actually, the gold standard method for an accurate detection of CNV is array CGH, but this technology cannot detect new point mutations. Exome sequencing can be used to detect CNV, but the lack of coverage in non-coding regions limits CNV detection sensitivity. Of note, whole genome sequencing can detect both CNVs and point mutations, but it is still very expensive and needs huge informatics capacities, which is an obvious limitation for a routine diagnostic use.For now, we have had to use two different methods in order to accurately detect both CNVs and point mutations. In other words, we have had to use precious samples two times, to assume the cost of two different methods (which is nearly 450 euros in the laboratory for exome sequencing, and a bit more for array CGH in a clinical laboratory), and to consider the time of the realization of two different methods in order to achieve a complete diagnostic.In this context, we aimed to develop an innovative sequencing method, named CoDE-seq (Copy number variation Detection and Exome sequencing), which would allow us to simultaneously detect both CNVs and point mutations, in order to reduce the time of diagnostic, the cost, and the needed quantity of sample.This work included the method conception, and the data analysis steps. The method conception has been done through the creation of a new capture enabling the detection of point mutations in the exome, and CNVs all along the genome. Furthermore, the data analysis step included the choice of the bioinformatics methods to be used, in order to get a specific and sensitive CNV detection, all along the genome.We were also interested in the fonctional significance of identified CNV, and tried to decipher it by the study of chromatine spacial conformation and the influence of these CNV.; La génétique, et par extension le séquençage de l’ADN, sont des outils qui ont transformé la compréhension des mécanismes impliqués dans la survenue de nombreuses pathologies, dont l’obésité. Les technologies aujourd’hui à notre disposition nous permettent de déterminer rapidement si un patient est ou non porteur d’un évènement génétique pouvant expliquer sa pathologie. L’une des techniques les plus utilisées en diagnostic aujourd’hui est le séquençage d’exome, ou WES, qui permet une excellente détection des mutations ponctuelles dans les régions codantes du génome. Mais d’autres évènements comme les copy number variants, ou CNV, peuvent également expliquer certaines pathologies, dont l’obésité, via entre autres les CNV de la région 16p11.2. Actuellement, la technique de référence pour la détection de ces copy number variants est l’analyse de puces CGH (Comparative Genomic Hybridization), mais celles-ci ne permettent pas de détecter des mutations non répertoriées au préalable lors de la création de la puce. Sur le principe, le séquençage d’exome peut lui aussi être utilisé pour détecter les CNV, mais son absence de couverture des régions non codantes du génome ne permet pas une détection efficace de ces CNV, car ceux-ci peuvent survenir sur l’ensemble du génome, en englobant des régions codantes et non codantes au sein d’un seul évènement. Le séquençage génome complet peut détecter ces deux types d’évènement, mais son cout est encore élevé ce qui freine sa démocratisation, et l’analyse de données associées nécessite d’importantes ressources informatiques, et le rend difficilement utilisable en diagnostic de routine en l’état actuel des choses. Il est donc pour l’instant nécessaire d’avoir recours à deux techniques différentes pour couvrir ces deux types d’évènements génétiques. Cela implique d’utiliser des échantillons parfois très précieux à deux reprises, de supporter les couts liés à deux techniques diagnostiques (d’environ 450 euros pour le séquençage d’exome au laboratoire et un cout un peu plus élevé pour une puce à ADN dans un laboratoire clinique), et d’allonger les temps de rendu de résultats et donc la durée d’établissement du diagnostic du patient. Cet état de fait nous a conduit à développer une technique de séquençage, que nous avons nommé CoDE-seq (Copy number variation Detection and Exome sequencing), et qui permettra la détection simultanée de ces deux types d’évènements, pour diminuer les temps d’établissement de diagnostics, leurs couts, et la quantité d’échantillon nécessaire. Ce travail a nécessité deux aspects : la mise au point technique et la mise au point analytique. La mise au point technique est passée par la création d’une nouvelle « capture », permettant une détection correcte des mutations ponctuelles de l’exome et des CNV de tout le génome. La mise au point analytique a consisté à définir la méthode à employer, et à permettre d’arriver à une détection fiable, à la fois sensible et spécifique, des CNV sur l’ensemble du génome. Une fois ces CNV identifiés, la question de leur signification fonctionnelle se pose également, et une seconde partie de ma thèse porte sur l’étude de cette signification fonctionnelle, via l’étude de la conformation spaciale de la chromatine et de l’influence des CNV sur celle-ci.

International audience; The worldwide obesity epidemic has been mainly attributed to lifestyle changes. However, who becomes obese in an obesity-prone environment is largely determined by genetic factors. In the last 20 years, important progress has been made in the elucidation of the genetic architecture of obesity. In parallel with successful gene identifications, the number of gene–environment interaction (GEI) studies has grown rapidly. This paper reviews the growing body of evidence supporting gene–environment interactions in the field of obesity. Heritability, monogenic and polygenic obesity studies provide converging evidence that obesity-predisposing genes interact with a variety of environmental, lifestyle and treatment exposures. However, some skepticism remains regarding the validity of these studies based on several issues, which include statistical modelling, confounding, low replication rate, underpowered analyses, biological assumptions and measurement precision. What follows in this review includes (1) an introduction to the study of GEI, (2) the evidence of GEI in the field of obesity, (3) an outline of the biological mechanisms that may explain these interaction effects, (4) methodological challenges associated with GEI studies and potential solutions, and (5) future directions of GEI research. Thus far, this growing body of evidence has provided a deeper understanding of GEI influencing obesity and may have tremendous applications in the emerging field of personalized medicine and individualized lifestyle recommendations.

OBJECTIVE Meta-analyses of genome-wide association studies in Europeans have identified > 98 loci for BMI. Transferability of these established associations in Pima Indians was analyzed. METHODS Among 98 lead single nucleotide polymorphisms (SNPs), 82 had minor allele frequency ≥ 0.01 in Pima Indians and were analyzed for association with the maximum BMI in adulthood (n = 3,491) and BMI z score in childhood (n = 1,958). Common tag SNPs across 98 loci were also analyzed for additional signals. RESULTS Among the lead SNPs, 13 (TMEM18, TCF7L2, MRPS33P4, PRKD1, ZFP64, FTO, TAL1, CALCR, GNPDA2, CREB1, LMX1B, ADCY9, NLRC3) were associated with BMI (P ≤ 0.05) in Pima adults. A multi-allelic genetic risk score (GRS), which summed the risk alleles for 82 lead SNPs, showed a significant trend for a positive relationship between GRS and BMI in adulthood (beta = 0.48% per risk allele; P = 1.6 × 10-9 ) and BMI z score in childhood (beta = 0.024 SD; P = 1.7 × 10-7 ). GRS was significantly associated with BMI across all age groups ≥ 5 years, except for those ≥ 50 years. The strongest association was seen in adolescence (age 14-16 years; P = 1.84 × 10-9 ). CONCLUSIONS In aggregate, European-derived lead SNPs had a notable effect on BMI in Pima Indians. Polygenic obesity in this population manifests strongly in childhood and adolescence and persists throughout much of adult life.

Except in rare cases, obesity tends to be a consequence of both an unhealthy lifestyle and a genetic susceptibility to gain weight. With more than 200 common genetic variants identified, there is a growing interest in developing personalized preventive and treatment strategies to predict an individual's obesity risk. We review the literature on the prediction of obesity and show that models based on the established genetic variants have poorer predictive ability than traditional predictors, such as family history of obesity and childhood obesity. Current findings suggest that opportunities for precision medicine in common obesity may be limited.

There is a pressing need for new effective therapeutic strategies for addressing the epidemic of type 2 diabetes. Leptin has been shown to reduce hyperglycaemia in rodent models of type 1 diabetes and has recently been shown to normalize fasting plasma glucose concentrations in a rodent model of polygenic obesity and type 2 diabetes. Overall, these findings suggest that leptin may be an effective therapeutic option for both type 1 and type 2 diabetes. However, short-term human clinical studies in overweight and obese patients with recently diagnosed type 2 diabetes have reported minimal efficacy of leptin administration to lower blood glucose levels. Herein, the role of leptin in the maintenance of glucose homeostasis and the potential use of leptin in the treatment of type 2 diabetes are discussed.

Induction of skeletal muscle (SM) mitochondrial stress by expression of uncoupling protein 1 (UCP1) in mice results in a healthy metabolic phenotype associated with increased secretion of FGF21 from SM. Here, we investigated whether SM mitochondrial uncoupling can compensate obesity and insulin resistance in the NZO mouse, a polygenic diabesity model. Male NZO mice were crossed with heterozygous UCP1 transgenic (tg) mice (mixed C57BL/6/CBA background) and further backcrossed to obtain F1 and N2 offspring with 50 and 75 % NZO background, respectively. Male F1 and N2 progeny were fed a high-fat diet ad libitum for 20 weeks from weaning. Blood glucose was reduced, and diabetes (severe hyperglycemia >300 mg/dl) was fully prevented in both F1- and N2-tg progeny compared to a diabetes prevalence of 15 % in F1 and 42 % in N2 wild type. In contrast, relative body fat content and plasma insulin were decreased, and glucose tolerance was improved, in F1-tg only. Both F1 and N2-tg showed decreased lean body mass. Accordingly, induction of SM stress response including FGF21 expression and secretion was similar in both F1 and N2-tg mice. In white adipose tissue, expression of FGF21 target genes was enhanced in F1 and N2-tg mice, whereas lipid metabolism genes were induced in F1-tg only. There was no evidence for induction of browning in either UCP1 backcross. We conclude that SM mitochondrial uncoupling induces FGF21 expression and prevents diabetes in mice with a 50-75 % NZO background independent of its effects on adipose tissue.

The molecular genetic analysis of obesity has led to the identification of a limited number of confirmed major genes. While such major genes have a clear influence on the development of the phenotype, the underlying mutations are however (extremely) infrequent and thus of minor clinical importance only. The genetic predisposition to obesity must thus be polygenic; a number of such variants should be found in most obese subjects; however, these variants predisposing to obesity are also found in normal weight and even lean individuals. Therefore, a polygene can only be identified and validated by statistical analyses: the appropriate gene variant (allele) occurs more frequently in obese than in non-obese subjects. Each single polygene makes only a small contribution to the development of obesity. The 103Ile allele of the Val103Ile single nucleotide polymorphism (SNP) of the melanocortin-4 receptor gene (MC4R) was the first confirmed polygenetic variant with an influence on the body mass index (BMI); the more common Val103 allele is more frequent in obese individuals. As determined in a recent, large-scaled meta-analysis the effect size of this allele on mean BMI was approximately -0.5 kg/m(2). The first genome-wide association study (GWA) for obesity, based on approximately 100,000 SNPs analyzed in families of the Framingham study, revealed that a SNP in the proximity of the insulin-induced gene 2 (INSIG2) was associated with obesity. The positive result was replicated in independent samples; however, some other study groups detected no association. Currently, a meta-analysis is ongoing; its result will contribute to the evaluation of the importance of the INSIG2 polymorphism in body weight regulation. SNP alleles in intron 1 of the fat mass and obesity associated gene (FTO) confer the most relevant polygenic effect on obesity. In the first GWA for extreme early onset obesity we substantiated that variation in FTO strongly contributes to early onset obesity.

The rapid development of new concepts and tools has led to a change in the way in which researchers carry out nutrition-related research. Obesity is determined by the interaction between predisposing genetic and environmental aspects, but at present the gene–gene and gene–environment interactions contributing to the development of this complex disease cannot be analysed in detail. The purpose of the present paper is to provide some examples of the knowledge that is available in the field of obesity genetics, and also the new strategies being developed that are aimed at studying the relative contribution of numerous genes to obesity and their responses to environmental changes. In the rare cases of monogenic obesities in which a major gene is the cause the molecular approach has proved extremely powerful in the identification of the genes responsible and in defining new syndromes. However, in the common forms of obesity (polygenic obesity) most studies have analysed genotype–phenotype associations without sometimes taking into account the influence of environmental factors (diet, sedentary lifestyle). Among the aspects limiting this integrated approach to obesity are the difficulty of having large enough samples and the expansion of biocomputing tools developed for accessing the question of multiple interactions with noa priorihypotheses. This picture is rapidly changing. Large databases of clinical data and DNA and biological sample banks with more precise environmental information and patient phenotypes are being compiled. The capacity for studying multiple genes simultaneously at the DNA or RNA levels is also possible. Finally, the tremendous progress in biocomputing will allow the integration of these different types of data (relating to environment, phenotype, genotype, gene expression) and will improve the ability to deal with this complex disease.

Obesity prevalence continues to increase worldwide, yet few safe and effective treatment options are available suggesting there needs to be a greater emphasis on preventing rather than treating obesity. This research investigated the association of obesity predisposing SNPs and a gene score with nutrient consumption patterns including total energy intake and macronutrient distribution in a European ancestry population as well as discussing an evolutionary perspective on eating disorders using current epidemiological evidence to identify genes which may be involved. The association of two of the 14 obesity predisposing SNPs and the gene score with BMI was confirmed in the EpiDREAM population. Novel associations between two SNPs located in or near BDNF (rs6265 and rs1401635) were found with total fat, MUFA, and PUFA intake. Rs1401635 was also associated with total energy and trans fat intake. Novel associations of rs6235 (PCSK1) and the gene score were found with total energy intake. The novel associations found indicate that food related behaviours are one of the mechanisms of action through which obesity predisposing SNPs cause obesity and therefore warrant further investigation. The lack of association among all genes and the modest association of the gene score show that mechanisms other than food consumption are important. The investigation of the evolutionary history of eating disorders revealed that the adapted to flee famine hypothesis is a plausible theory explaining anorexia nervosa while the thrifty genotype hypothesis provides a possible explanation for bulimia nervosa and binge eating disorder. These evolutionary theories can be applied to identify new candidate genes as well as phenotypic traits to investigate to better understand the genetic architecture of eating disorders. Understanding genes associated with disordered eating patterns may highlight future areas for obesity prevention. Thesis Master of Science (MSc) A large percentage of the risk of developing obesity or an eating disorder (anorexia nervosa, bulimia nervosa, and binge eating disorder) is determined by genetics. For obesity, many genes have been identified as influencing risk, but the mechanisms through which the genes work are largely unknown. For eating disorders, gene identification efforts have been mostly unsuccessful and no mechanisms of action have been determined. In the first component of this thesis we found an association between previously identified obesity risk genes and food intake, specifically the total number of calories consumed per day and the percentage of calories from total fat and fat subtypes. These results support that food related behaviours are possible mechanisms of action which need to be further investigated. In the second half of the thesis we viewed eating disorder behaviours from an evolutionary perspective. We concluded that there are theories that possibly explain eating disorder behaviours including being able to live off of small quantities of food as well as binging. These evolutionary theories can be applied to identify new genes to study in the context of eating disorders as well as different definitions of eating disorders.

Our understanding of how the brain maintains energy homeostasis is based heavily on rodent genetic models. Increasingly research with these models has focused on gene–environment interactions including stress, diet, nutrition and maternal influences. Here, we review the evolution of transgenic mouse models to provide sophisticated spatial and temporal resolution to analyses of relevant neuroendocrine circuits. We also summarize advances in the environmental disruption of energy balance and the dissection of polygenic obesity in rodent models.

Objective: To characterize the phenotypic consequences of long-term selective breeding for rapid weight gain, with an emphasis on obesity and obesity-induced diabetes (diabesity). Research Methods and Procedures: M16 is the result of long-term selection for 3- to 6-week weight gain from an ICR base population. Experiment 1 characterized males from both lines for body weights (3, 6, and 8 weeks), feed (4 to 8 weeks) and H2O (6 to 8 weeks) consumption, and heat loss, body composition, and levels of several plasma proteins at 8 weeks of age. Experiment 2 characterized differences between lines for both sexes at three ages (6, 8, and 16 weeks) and fed two diets (high and normal fat). Body weight, composition, blood glucose, and plasma insulin and leptin levels were evaluated after an 8-hour fast. Results: At all ages measured, M16 mice were heavier, fatter, hyperphagic, hyperinsulinemic, and hyperleptinemic relative to ICR. M16 males and females were hyperglycemic relative to ICR, with 56% and 22% higher fasted blood glucose levels at 8 weeks of age. Discussion: M16 mice represent an outbred animal model to facilitate gene discovery and pathway regulation controlling early onset polygenic obesity and type 2 diabetic phenotypes. Phenotypes prevalent in the M16 model, with obesity and diabesity exhibited at a young age, closely mirror current trends in human populations.

Obesity is an important cause of morbidity and mortality in developed countries, and is also becoming increasingly prevalent in the developing world. Although environmental factors are important, there is considerable evidence that genes also have a significant role in its pathogenesis. The identification of genes that are involved in monogenic, syndromic and polygenic obesity has greatly increased our knowledge of the mechanisms that underlie this condition. In the future, dissection of the complex genetic architecture of obesity will provide new avenues for treatment and prevention, and will increase our understanding of the regulation of energy balance in humans.