Handbook of Eating Disorders - part 2 pptx

36 ELIZABETH WINCHESTER AND DAVID COLLIER Polygenic traits will be continuously distributed in the population, i.e. they are quantitative traits. However, many complex diseases are qualitative (dichotomous) disorders, where you either have or do not have the disease, but are also polygenic. A liability-threshold model has been proposed for polygenic dichotomous diseases. In this model the underlying polygenic liability is continuously (normally) distributed in the population (i.e. there is a continuum of genetic risk) and there is a threshold of liability (Plomin et al., 2001). A disease will only develop when the number of susceptibility alleles exceeds the liability threshold. Gene–gene interactions (epistasis), in which a gene variant will only confer susceptibility in the presence of another gene variant, and gene–environment interactions, in which susceptibility alleles will have their deleterious effects only in the presence of a particular environmental factor, are likely to be involved in the predisposition to complex diseases. Environmental factors are important and complex diseases will develop in those carrying the greatest genetic and environmental loading. HERITABILITY OF COMPLEX DISEASES Family, twin and adoption studies are used to determine the relative contribution of genetic and environmental risk factors in the aetiology of complex diseases, such as eating disorders and obesity (Plomin et al., 2001). In family studies the frequency of a disease in the relatives of an affected individual is compared with the frequency in the general population. A higher disease frequency in relatives compared to the general population provides evidence for a genetic susceptibility to a disease. However, familial aggregation of a disease could also be explained by shared family environment. Twin and adoption studies are powerful methods of disentangling genetic from environmental sources of family resemblance (Plomin et al., 2001). In twin studies, the similarity of monozygotic (MZ) (genetically identical) twin pairs is compared with the similarity of dyzygotic (DZ) (non-identical) twin pairs for a particular trait. MZ twin pairs share all of their genes and DZ twin pairs share, on average, half of their genes. Therefore, MZ twin pairs will be more similar than DZ twin pairs for a trait that is, to some extent, influenced by genetic factors. However, MZ twin pairs may share a more similar environment than DZ twin pairs. The greater resemblance of MZ twins could therefore be caused by environmental factors that are experienced by MZ twin pairs but not by DZ pairs. To ensure that the greater similarity in MZ twins reflects shared genetic factors, twin studies should demonstrate that both types of twins are equally exposed to aetiological environmental factors (Plomin et al., 2001). This is known as the equal environment assumption (EEA), one of several assumptions in twin methodology. Violation of the EEA would exaggerate estimates of genetic influence. In adoption studies the resemblance of genetically related individuals who do not share a common family environment, e.g. adopted children and their genetic parents, or the resem- blance of family members who are not genetically related but share the same environment, e.g. adopted children and their adoptive parents, are examined. The former situation will estimate the genetic contribution and the latter the postnatal environmental contribution to familial resemblance. In twin and adoption studies the size of the genetic and environmental effects are cal- culated by comparing sets of phenotypic correlations between different types of relative GENETIC AETIOLOGY OF EATING DISORDERS AND OBESITY 37 pairs. The relative proportion of phenotypic variance that is attributable to additive genetic effects (the cumulative influence of multiple individual genes), shared environmental effects (factors that are common to both members of relative pair), and non-shared environmental effects (influences that are unique to one member of a relative pair), can be estimated from these comparisons. There is insufficient statistical power in twin and adoption analyses to estimate other genetic influences, such as gene–gene interactions (epistasis) and dominance effects. The proportion of the total variation of a trait that is attributable to additive genetic factors is known as the heritability of a trait and provides an indication of the importance of genetic factors. A detailed description of twin and adoption methodology is beyond the scope of this chapter but is discussed in detail in Plomin et al. (2001). HERITABILITY OF EATING DISORDERS Family Studies of Eating Disorders The majority of family studies have shown that eating disorders are familial (reviewed by Strober et al., 2000). In the largest case-control family study to date, the risk for AN in female relatives of anorexic probands was 11.4 times higher than the risk in the relatives of control subjects, and the risk for BN in female relatives of bulimic probands was 3.7 times higher (Strober et al., 2000). Some family studies have also reported familial aggregation of milder, broader (subthreshold) phenotypes of AN and BN among female relatives of AN and BN probands respectively (Stein et al., 1998; Strober et al., 2000). Cross-transmission of eating disorders in families is evident from family and twin studies suggesting that AN and BN share or have common familial aetiologic factors (Walters & Kendler, 1995). The prevalence of full and subthreshold BN has been shown to be greater in female relatives of AN probands than in the relatives of control subjects, and the converse for relatives of BN probands (Strober et al., 2000; Walters & Kendler, 1995). Based on the above observations it has been proposed that the full and subthreshold forms of eating disorders form a spectrum of clinical severity in which there is a continuum of familial liability (Strober et al., 2000). The familial aggregation of full and subclinical eating disorders suggests that genetic factors are likely to be involved in causation. The relative contribution of genetic and environmental factors in the aetiology of eating disorders has been determined in twin studies. Twin Studies of AN and BN Different estimates of heritability have been obtained from twin studies of AN. The re- liability of these estimates are limited due to the ascertainment bias, small sample sizes, or violation of the EEA in several of these studies (Fairburn et al., 1999). In a study of clinically ascertained twins, concordance for AN was substantially greater in MZ twin pairs than in DZ twin pairs, and the heritability was estimated at about 70% (Treasure & Holland, 1989). In contrast, a population-based study of twins found that the concordance rates for AN were higher in DZ twins than in MZ twin pairs (Walters & Kendler, 1995). However, due to the small sample size, the rarity of AN and the possible violation of the EEA in this study inferences regarding the aetiology of AN have not been made from these 38 ELIZABETH WINCHESTER AND DAVID COLLIER results (Fairburn et al., 1999). The heritability of AN was estimated to be 76% in another population-based twin sample (Klump et al., 2001) and 58% in a bivariate analysis of AN and major depression (Wade et al., 2000). The magnitude of the genetic contribution to AN remains unresolved. Large-scale twin studies are needed to define the extent and nature of the genetic and environmental contributions to the aetiology of AN. Three clinically ascertained twin pair studies of BN (Fichter & Noegal, 1990; Hsu et al., 1990; Treasure & Holland, 1989) and two population-based twin studies of BN (Wade et al., 1999; Bulik et al., 1998; Kendler et al., 1991, 1995) have been conducted and have consistently demonstrated significant genetic contributions in the liability to BN. Reanalysis of the data from the twin studies of BN produced estimates of heritabilty ranging from 31% to 83% (Bulik et al., 2000). In general non-shared environmental effects were shown to account for the remaining variance in liability to BN. The magnitude of the contribution of shared environmental effects is unclear but in the majority of the twin studies it appears to be less important than additive genetic effects and non-shared environmental effects (Bulik et al., 2000). Several of the symptoms, behaviours and attitudes associated with disordered eating have been shown to be heritable in different populations of twins. These continuous traits are assessed using psychometric questionnaires, such as the Eating Disorder Inventory (EDI; Garner et al., 1984) and the Eating Disorders Examination (EDE; Fairburn & Cooper, 1993). The Drive for Thinness subscale of the EDI, was shown to be heritable in one twin population (Holland et al., 1988), and in another twin study several EDI subscales showed heritabilities ranging from 28% to 52% (Rutherford et al., 1993). Heritabilities of 46% and 70% have been reported for binge eating and self-induced vomiting respectively (Sullivan et al., 1998). There is evidence of age-related differences in genetic and environmental influences on these traits. Marked differences in heritabilities for EDI subscales have been reported for a preadolescent (aged 11 years) and an adolescent (aged 17 years) twin sample from the same population (Klump et al., 2000). The contribution of additive genetic effects for the EDI subscales was greater in the adolescent twin sample than in the preadolescent group. Based on this finding it has been proposed that puberty may activate the heritability of eating disorders (Klump et al., 2001). Measures from the EDE such as dietary restraint, and concerns about eating, weight and shape also appear to be heritable (Wade et al., 1998). Several family and twin studies have investigated the causes of comorbidity between eating disorders and personality traits and other psychiatric disorders. Family studies in- vestigating the relationship between personality traits and eating disorders have shown that some personality traits are significantly elevated in the unaffected relatives of probands with an eating disorder compared to the relatives of the control group (Kaye et al., 1999; Lilenfeld et al., 2000). For example perfectionism, ineffectiveness, and interpersonal dis- trust has been found to be significantly elevated in the unaffected relatives of BN probands compared to the relatives of the control group (Lilenfeld et al., 2000). There is evidence to suggest that the familial cotransmission of eating pathology and some personality traits results from the sharing of common genetic risk factors. Results from twin studies suggest that the comorbidity between AN and major depression and between BN and major depres- sion is most likely due to genetic factors that influence both disorders (Wade et al., 2000; Walters et al., 1992). It is evident from these studies that there are also unique genetic effects influencing eating disorders that are independent of those contributing to the personality traits and psychiatric disorders. GENETIC AETIOLOGY OF EATING DISORDERS AND OBESITY 39 Model of Inheritance of Eating Disorders Overall family and twin studies provide evidence for a genetic contribution to the aetiology of eating disorders. However the magnitude of the genetic effect remains uncertain because of problems with case ascertainment and the low statistical power of the studies to date. Non-shared environmental effects appear to play a substantial role in the liability to eating disorders. The development of eating disorders is likely to involve interactions between multiple environmental and genetic risk factors. HERITABILITY OF HUMAN OBESITY Family, Twin and Adoption Studies Family, twin, and adoption studies have indicated that genetic factors play a significant role in the aetiology of obesity and obese phenotypes (Echwald, 1999). Once again in these studies estimates of heritability vary, and thus the relative importance of genetic factors in the causation of obesity remain controversial. Obesity shows strong familial aggregation but, except for rare monogenic forms of obe- sity, it does not exhibit a clear pattern of Mendelian inheritance. Many family studies have shown that the risk of obesity (BMI > 30) is higher in the biological relatives of obese indi- viduals compared to the risk in the general population (reviewed in Ravussin & Bouchard, 2000). Overall, family studies have shown that between 20 and 50% of the variation in obesity phenotypes is attributable to genetic factors (reviewed in Echwald, 1999). Twin studies have reported the highest estimates of heritability for obese phenotypes. In a review of twin studies, concordance rates for BMI were higher in MZ twin pairs than in DZ twin pairs and the heritability estimates ranged from 50% to 90% (Barsh et al., 2000). Adoption studies suggest that shared environment in childhood has much less effect on BMI than genes (Echwald, 1999). Model of Inheritance for Obesity The segregation of obesity in families is consistent with a polygenic model of inheritance, with the exception of the rare Mendelian (caused by a single-gene mutation) forms of obesity (Comuzzie & Allison, 1998; Echwald, 1999). The polygenic component of obesity is likely to involve multiple additive gene variants, each of which has a small effect on phenotypic variation, and interacts with other genes and environmental factors. Each gene variant is neither sufficient nor necessary for the development of obesity (Sorensen & Echwald, 2001). Its is clear from the heritability estimates of obesity that environmental factors are im- portant to the aetiology of obesity. However, the relative genetic and environmental contri- butions remain unclear. Epidemiological studies indicate that obesity is strongly influenced by environmental factors. For example, differences in prevalence of obesity between popu- lations and between different groups within populations are closely associated with socio- economic and behavioural factors (Sorensen & Echwald, 2001). The rising epidemic of obesity throughout the western world and developing countries cannot be explained by 40 ELIZABETH WINCHESTER AND DAVID COLLIER recent changes in genetic inheritance but as a result of rapid environmental changes, such as the availability and composition of food. A model of the development of obesity has been proposed, in which susceptibility to obesity is mainly determined by genetic factors but a favourable environment is necessary for the expression of the genetic predisposition (Barsh et al., 2000). This putative inter- action between genes and environment suggests that the effects of a high level of genetic susceptibility would be amplified in a high-risk environment. Based on this model the rising prevalence of obesity can be explained by environmental changes that have led to the full ex- pression of an underlying pool of obesity susceptibility genes. A good example are the Pima Indians living in the USA who have a much higher prevalence of obesity and type 2 diabetes than the Pima Indians living in Mexico, where food availability is restricted (Ravussin & Bouchard, 2000). There has been much speculation over why the human genome contains genetic variants that predispose to obesity. One explanation is the ‘thrifty genotype hypoth- esis’ (Neel, 1962). This hypothesis suggests that evolution through alternating periods of famine with periods of food abundance positively selected for genetic variants that confer survival advantages in famine periods, e.g. ‘thrifty genes’ (Ravussin & Bouchard, 2000). These ‘thrifty genes’ are deleterious in modern western societies where calorie-rich foods are abundant. MOLECULAR GENETIC METHODOLOGY FOR IDENTIFYING SUSCEPTIBILITY GENES FOR COMPLEX DISEASES Two convergent approaches are used to identify gene variants contributing to the suscepti- bility of complex diseases: linkage and association studies. Candidate genes for a complex trait are genes that have been implicated in the pathophysiology of a disease based on ge- netic, physiological or pharmacological evidence. The role of a candidate gene in a complex disorder can be examined in targeted linkage studies and/or association studies. Linkage Studies Non-parametric (‘model-free’) methods of linkage analysis are used for complex traits because this method does not require prior knowledge about the inheritance of a disease. In non-parametric linkage analysis the segregation of variants of anonymous, highly variable deoxyribonucleic acid (DNA) loci (marker alleles) is examined in affected family member pairs, e.g. affected sister pairs. Marker alleles shared by affected relative pairs more often than would be expected by chance provide evidence that there is a linkage between the marker and the disease under investigation, which can either be a dichotomous complex trait or a quantitative trait. The affected sib-pair design is the most widely used approach. Linkage analysis is a statistical approach involving the calculation of LOD scores, which are the logarithms to the base 10 of the likelihood ratios for linkage verses non-linkage. For complex diseases LOD scores >3.3 are considered the most appropriate threshold for evidence of significant linkage (Lander & Kruglyak, 1995). This threshold for significance minimizes the risk of false positive results. GENETIC AETIOLOGY OF EATING DISORDERS AND OBESITY 41 In genome-wide linkage studies DNA markers spaced at regular intervals throughout the genome are examined in affected relative pairs. The DNA markers with significant linkages identify novel candidate chromosomal regions (susceptibility loci) that may en- compass unknown or unexpected susceptibility genes. Quantitative trait loci (QTL), which are chromosomal regions that may contain genes that contribute to a quantitative trait, can be identified in genome-wide linkage studies using sib-pairs who both have extreme scores on a measure of a quantitative trait. QTL linkage analysis is a powerful approach for identifying genetic variants with a small to moderate effect on phenotypic variance be- cause quantitative traits are more likely to have a direct relationship with individual genetic variants. In targeted sib-pair linkage studies the segregation of a genetic variant of a candidate gene or a marker allele close to a candidate gene is examined in affected relative pairs. Association Studies Two sample designs are used in association studies: case controls and family trios. Both designs are used to evaluate the role of variants of candidate genes in a complex disorder. In case-control association studies the frequency of a genetic variant of a gene (an allele) or marker allele in an affected group is compared with the frequency of the allele in a control group from the same population. An allele, which is either directly involved in the genetic susceptibility of a disease, or closely linked to the causative allele, will occur more often in cases than in controls than would be expected by chance. The differences in allele frequencies between cases and controls are tested for statistical significance using a statistical measure such as the chi-squared or odds ratio test. The risk of false positive or false negative findings is a major problem with case-control association studies, particularly in studies based on small sample sizes or in studies using a heterogeneous population where the cases and controls may consist of genetically distinct subsets, e.g. different ethnic groups (Barsh et al., 2000). The problem of poor matching between cases and controls can be overcome by using family trios, which consist of an affected child and both parents. In family-based (family trios) association studies the alleles that the parents do not pass onto their child act as internal controls. The risk of false negative results is inherent in the low- frequency and small biological impact of the genetic variants involved in the susceptibility of complex diseases (Sorensen & Echwald, 2001). Hence it is important that candidate genes are not excluded on the basis of negative findings and that positive associations are replicated in different samples to confirm true associations. For both linkage and association studies of complex traits, large sample sizes are needed to provide sufficient statistical power to detect genetic variants that confer a small effect on phenotypic variance. CHOOSING THE PHENOTYPE FOR MOLECULAR GENETIC STUDIES The definition of the phenotype or the diagnostic criteria used to classify individuals as affected or unaffected is an important consideration when designing molecular genetic 42 ELIZABETH WINCHESTER AND DAVID COLLIER research strategies for complex diseases. It is important that the diagnostic criteria used in genetic studies are robust and reliable, so that results from different studies are comparable. Eating Disorders The eating disorders have been classified into three categories: anorexia nervosa, bulimia nervosa and binge eating disorder (DSM-IV; APA, 1994). Subgroups within the AN and BN groups have been defined on the basis of variations in eating and compensatory be- haviours. Individuals with AN are divided into those with restricting AN (RAN) and those with binge-purging AN (AN/BP). Individuals with BN are divided into a purging type in which individuals engage in laxative abuse, self-induced vomiting and/or enemas, and a non-purging type where individuals engage in fasting or extreme exercise. Although this diagnostic classification system is useful for genetic research, it has many pitfalls and ap- pears to be somewhat arbitrary. The difficulties with categorizing the eating disorders are discussed in depth in other chapters in this book. Firstly, AN and BN are not discreet dis- orders and approximately 50% of women with AN develop BN over the course of their illness (Treasure & Collier, 2001). The boundaries between other eating disorder categories also overlap. For example, it is difficult to distinguish between non-purging BN and BED. Secondly, a substantial proportion of the individuals presenting with an eating disorder do not fulfil the diagnostic criteria for the main categories and are classified as having an eating disorder not otherwise specified (EDNOS). This group includes individuals presenting with ‘partial syndromes’. It has been proposed that it might be more appropriate to view all eating disorders as lying on a spectrum with a continuum of eating symptoms from under-eating to over-eating (Treasure & Collier, 2001). It is conceivable that many of the differences between eating disorder categories, such as between BN and obesity, may be quantitative rather than qualitative. Several of the personality traits and Axis II disorders that are frequently associated with eating disorders have been shown to precede the development of eating disorders and to persist after long-term recovery, suggesting that they could contribute to the pathogenesis of eating disorders (Kaye et al., 2000a). It has been suggested that eating disorders should not only be classified in terms of eating symptoms but also by personality types. Three personality domains have been identified: a high functioning, self-critical, perfectionistic group, which was mainly associated with BN; a constricted, overcontrolled group restricting pleasure, needs, emotions, relationships and self-knowledge, which was associated with RAN; and an impulsive, undercontrolled and emotionally dysregulated group (Goldner et al., 1999). Defining the phenotype for eating disorder research is far from simple. Many genetic studies to date have used eating disorder subgroups such as RAN, AN/BP, binge-purging BN, or non-purging BN because the genes underlying these types are likely to be more homogeneous than those underlying the main eating disorder categories. The use of narrow diagnostic criteria increases the chance of detecting small genetic effects. However, the number of individuals in each subgroup would be very small because AN and BN are rare and this would reduce the statistical power of the study. Conversely, a broad eating disorder phenotype that includes ‘partial symptoms’ would increase the sample size but the heterogeneity of the sample would reduce statistical power. Future research may benefit from conceptualizing the eating disorders as a spectrum. GENETIC AETIOLOGY OF EATING DISORDERS AND OBESITY 43 Obesity Obesity and obesity-related phenotypes are quantitative traits. The use of quantitative traits, where the effects of individual genes may be more pronounced, increases the statistical power of genetic studies (Barsh et al., 2000). There are several different measures of obesity and related phenotypes. The most widely used measure of general obesity is the body mass index (BMI), which is defined as the weight in kilograms (kg) divided by body area. In practice the BMI is usually estimated by dividing the weight (kg) by the height squared (m 2 ). This measure is reliable, inexpensive and convenient for large sample numbers, however it does not account for the proportion of fat to muscle mass in the body and is influenced by factors unrelated to obesity, e.g. organ mass (Perusse & Chagnon, 1997). The total amount of body fat mass expressed as a percentage of the total body weight (% FAT) is a more accurate measure of obesity and can be assessed from underwater weighing or bioelectrical impedance. The amount of subcutaneous fat distribution can be assessed by the sum of skinfold thickness measured at different sites around the body or various skinfold ratios (Perusse & Chagnon, 1997). Abdominal obesity is measured using the ratio of waist to hip circumference (WHR) and waist circumference, which is the best correlate of visceral fat (Despres et al., 2001). Intermediary phenotypes, which relate more to the underlying physiology of obesity, such as resting metabolic rate (RMR), respiratory quotient (RQ), insulin sensitivity, and leptin levels can also be measured and are often used in molecular genetic studies. The different obesity-related phenotypes are likely to have unique and shared genetic risk factors. The heritable personality traits often associated with eating disorders and other eating disorder symptoms that appear to have a heritable component, such as drive for thinness, are quantitative traits and can be used in QTL analysis for the eating disorders. Multiple quantitative phenotypes can be analysed to increase the statistical power of linkage and association studies. However, multiple comparisons will be necessary, which raises the threshold required to achieve statistical significance and this will result in a reduction in power. IDENTIFICATION OF SUSCEPTIBILITY GENES FOR EATING DISORDERS AND OBESITY Genetic research into eating disorders is in its infancy and to date only one genome-wide linkage study has been completed for eating disorders, the results of which have not yet been published. However, other genome-wide linkage studies in large populations are currently underway. Several candidate gene association studies have been completed, but the majority have reported negative findings. Two approaches have been adopted in obesity research: one has studied the rare single- gene (monogenic) mutations causing obesity in rodents and in humans, and the other has studied the genetics of common variation in body weight. Identification of some of the genes responsible for Mendelian forms of obesity in rodents and humans has directly resulted in the unravelling of a fundamental pathway involved in body weight regulation (Barsh et al.,2001). In the effort to identify genetic variants contributing to common obesity, QTL have been mapped in human populations and in polygenic animal models of obesity and 44 ELIZABETH WINCHESTER AND DAVID COLLIER many candidate genes have been evaluated in linkage and association studies. A forum known as the ‘Human Obesity Gene Map’ has been established, in which the results from all the published studies on the genetics of obesity are collected with the aim of helping to guide the design of future studies (Perusse et al., 2001). Remarkable progress has been made over the last decade in understanding the genetic mechanisms underlying human body weight regulation (Barsh et al., 2000). As a result of these discoveries, candidate gene analyses for eating disorders and obesity have focused on the genes involved in both the central and peripheral control of energy intake and expenditure. This section will summarize: r The monogenic causes of obesity in rodents and humans r The association and linkage results for the genes involved in body weight regulatory pathways r Other candidate genes for eating disorders r Other candidate genes for obesity r Obesity QTL identified in human populations through genome-wide linkage studies and in polygenic animal models of obesity r The search for lean genes. Mongenic Rodent Models of Obesity The genes responsible for six naturally occurring single-gene (monogenic) mutation mouse models of obesity have been identified and their protein products characterized (Table 3.1). The human homologues of these mouse obesity genes have been isolated and several muta- tions in the LEP and LEPR genes have been found as rare causes of human obesity (Perusse et al., 2001). Isolation of the mouse Lep gene from the Obesity (ob) mutation, the human homologue, LEP, and the characterization of the gene product as a circulating satiety pro- tein, now named leptin (from the Greek word for thin, leptos), was a major breakthrough in Table 3.1 Monogenic mouse models of obesity Chromosomal Protein Mouse Mouse Human location in product of mutation gene homologue humans gene References Obese (ob) Lep LEP 7q31.3 Leptin Zhang et al. (1994) Diabetes (db) Lepr LEPR 1p31 Leptin receptor Chen et al. (1996) Agouti yellow (A y ) A y 20q11.2–q12 Agouti-signalling protein Wilson et al. (1995) Fat (fat) Cpe CPE 4q32 Carboxy- peptidase Naggert et al. (1995) Tubby (tub) Tub TUB 11p15.5 Insulin-signalling protein Kleyn et al. (1996); Kapeller (et al.) 1999 Mahogany (mg) Atrn ATRN 20p13 Attractin Nagle et al. (1999); Gunn et al. (1999) GENETIC AETIOLOGY OF EATING DISORDERS AND OBESITY 45 obesity research (Zhang et al., 1994). Leptin is truncated and inactive in mutant ob/ob mice (Zhang et al., 1994) and treatment with recombinant leptin results in weight reduction in these obese mice (Halaas et al., 1995). The characterization of the mouse gene responsible for the Diabetes (db) mutation as the leptin receptor (Chen et al., 1996), confirmed the prediction, made from earlier cross-circulation (parabiosis) experiments, that ob/ob mice might be deficient in a circulating signal of satiety and db/db mice might be deficient in its cognate receptor (Spiegelman & Flier, 2001). The discovery of leptin and its receptor immediately resulted in the recognition of a fun- damental endocrine feedback loop regulating the size of adipose (fat) tissue mass, known as the leptinergic–melanocortinergic system, that is conserved among all mammals (reviewed in chapters in this handbook and in Spiegelman and Flier, 2001). Leptin, which is expressed in adipose tissue and circulates in proportion to adipose tissue mass, serves as the affer- ent signal of this loop informing the brain about the status of the body’s fat stores. It acts through leptin receptors on nerve cells in the arcuate nucleus of the hypothalamus to trigger neuropeptide responses that modulate appetite and energy expenditure. Through identification of the other rodent obesity genes, knockout and transgenic mice studies and identification of mutant genes in human monogenic obesity, the neuropep- tides that coordinate the response to leptin signalling have been defined (Spiegelman & Flier, 2001). Leptin reduces expression of the orexigenic (feeding-inducing) neuropep- tides, neuropeptide Y (NPY) and agouti-related protein (AgRP) and induces expression of the anorexigenic (feeding-inhibitors) neuropeptides, cocaine and amphetamine related transcript (CART) and the melanocortin, α-melanocyte-stimulating hormone (α-MSH), via activation of proopiomelanocortin (POMC) neurons. α-MSH is derived from POMC, which is a precurser protein that is cleaved into a number of proteins with diverse physio- logical roles. α-MSH reduces food intake and increases energy expenditure through acti- vation of melanocortin 3 (Mc3) and melanocortin 4 (Mc4) receptors in the hypothalamus (Spiegelman & Flier, 2001). Knockout studies in mice have demonstrated that Mc3r and Mc4r have distinct and complementary roles in energy homeostasis (Chen et al., 2000). AgRP is an endogenous antagonist of the Mc3/4 receptors and thus opposes the action of α-MSH. The involvement of melanocortins in the leptin-signalling pathway was determined through elucidation of the genetic basis for the dominant agouti yellow (A y ) obesity syn- drome. The obesity in the A y mouse is caused by the abnormal expression of the A y gene product—the agouti coat-colour protein—in the brain where it mimics AgRP by antagoniz- ing the signalling of α-MSH through the melanocortin 4 receptor (Mc4r) (Michaud et al. 1994; Rossi et al., 1998). Pomc and Mc4r knockout mice and gain-of-function Agrp muta- tions in mice produce an obesity phenotype similar to that displayed by the A y mice, thereby supporting the central role of the melanocortin system in energy homeostasis (Graham et al., 1997; Huszar et al., 1997; Yaswen et al., 1999). The functional roles of the Fat ( fat) and Tubby (tub) mutations in causing obesity have not been clearly defined. The gene responsible for the fat mutation, Cpe, encodes carboxypepti- dase E, an enzyme involved in processing many neuropeptides, including POMC (Naggert et al., 1995). The fat mutation reduces enzyme activity and it has been proposed that the obesity in the fat mouse may be caused, in part, by defective POMC processing (Barsh et al., 2000). The protein product of the tub gene is an insulin-signalling protein, which is highly expressed in the hypothalamus and may be involved in the response to leptin (Kleyn et al., 1996; Kapeller et al., 1999). The attractin (Atrn) gene is responsible for the Mahogony [...]... anorexia nervosa, bulimia nervosa, and obesity 4q28–q31 11q 22. 2–q 22. 3 S NS NS ND ND NS 5q31–q 32 UCP -2 UCP-3 8p 12 p11 .2 ADR 2 UCP -2 /-3 11q13 11q13 UCP-1 DRD3 DRD4 DRD2 ADRβ3 ND ND ND ND ND ND a S, significant; NS, non-significant; ND, not done p-value for the association of the rare allele to the phenotype b See Perusse et al (20 01) for the Human Obesity Gene Map: The 20 00 Update This details all the association... Replication of linkage results in Table 3.3 Summary of some human QTL showing strong and suggestive evidence of linkage to obesity and obesity-related phenotypes Chromosomal location of QTL Obesity phenotype 2p21 Leptin, fat mass, BMI 20 q13 20 q11 .2 10p 12. 3 10p11 .22 11q24 11q 22 18q 12 BMI >30, %fat 24 -hour RQ Obesity Obesity BMI % Fat Fat free mass Lod scorea or p-value References Lod = 4.9 /2. 8 0.008 . nuerotransmitter 5-HT NS ND system SERT NS <0.000 5-HTR 2a 13q14–q21 0. 02 NS 0. 028 –0.047 0.005 0.0001 0.0001 NS in 3 studies 5-HTR 2c Xq24 NS NS BMI > 28 0.009–0. 02 Dopaminergic neurotransmitter DRD2 11q 22. 2–q 22. 3. 11q 22. 2–q 22. 3 ND ND Relative weight 0.0 02 system Obesity 0.0 02 0.003 Iliac and triceps 0.0 02 0.039 skinfold DRD3 NS ND DRD4 NS ND Thermogenesis UCP-1 4q28–q31 High fat gainers 0.05 BMI 0. 02 Weight. loss 0.001 UCP -2 11q13 Significant in 6 studies b UCP-3 11q13 BMI, RQ 0.008–0.04 BMI 0.0037 BMI 0. 02 0.04 UCP -2 /-3 SN D Lipid metabolism ADRβ 2 5q31–q 32 ND ND Significant in 9 studies b ADRβ3 8p 12 p11 .2 NS ND