Handbook of Eating Disorders - part 2 pptx

HERITABILITY OF COMPLEX DISEASES Family, twin and adoption studies are used to determine the relative contribution of geneticand environmental risk factors in the aetiology of complex di

36 ELIZABETH WINCHESTER AND DAVID COLLIERPolygenic traits will be continuously distributed in the population, i.e they are quantitativetraits However, many complex diseases are qualitative (dichotomous) disorders, where youeither have or do not have the disease, but are also polygenic A liability-threshold model hasbeen proposed for polygenic dichotomous diseases In this model the underlying polygenicliability 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 onlydevelop when the number of susceptibility alleles exceeds the liability threshold Gene–geneinteractions (epistasis), in which a gene variant will only confer susceptibility in the presence

of another gene variant, and gene–environment interactions, in which susceptibility alleleswill 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 factorsare important and complex diseases will develop in those carrying the greatest genetic andenvironmental loading

HERITABILITY OF COMPLEX DISEASES

Family, twin and adoption studies are used to determine the relative contribution of geneticand environmental risk factors in the aetiology of complex diseases, such as eating disordersand 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 higherdisease frequency in relatives compared to the general population provides evidence for agenetic susceptibility to a disease However, familial aggregation of a disease could also beexplained 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 iscompared with the similarity of dyzygotic (DZ) (non-identical) twin pairs for a particulartrait 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 atrait that is, to some extent, influenced by genetic factors However, MZ twin pairs mayshare a more similar environment than DZ twin pairs The greater resemblance of MZtwins could therefore be caused by environmental factors that are experienced by MZtwin pairs but not by DZ pairs To ensure that the greater similarity in MZ twins reflectsshared genetic factors, twin studies should demonstrate that both types of twins are equallyexposed to aetiological environmental factors (Plomin et al., 2001) This is known as theequal 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 acommon 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 willestimate the genetic contribution and the latter the postnatal environmental contribution tofamilial resemblance

In twin and adoption studies the size of the genetic and environmental effects are culated by comparing sets of phenotypic correlations between different types of relative

cal-GENETIC AETIOLOGY OF EATING DISORDERS AND OBESITY 37pairs The relative proportion of phenotypic variance that is attributable to additive geneticeffects (the cumulative influence of multiple individual genes), shared environmental effects(factors that are common to both members of relative pair), and non-shared environmentaleffects (influences that are unique to one member of a relative pair), can be estimated fromthese comparisons There is insufficient statistical power in twin and adoption analyses toestimate other genetic influences, such as gene–gene interactions (epistasis) and dominanceeffects 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 thescope 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 byStrober et al., 2000) In the largest case-control family study to date, the risk for AN infemale relatives of anorexic probands was 11.4 times higher than the risk in the relatives ofcontrol subjects, and the risk for BN in female relatives of bulimic probands was 3.7 timeshigher (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 ANand 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 ANand BN share or have common familial aetiologic factors (Walters & Kendler, 1995) Theprevalence 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 BNprobands (Strober et al., 2000; Walters & Kendler, 1995) Based on the above observations ithas 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 factorsare likely to be involved in causation The relative contribution of genetic and environmentalfactors 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 liability of these estimates are limited due to the ascertainment bias, small sample sizes,

re-or violation of the EEA in several of these studies (Fairburn et al., 1999) In a study ofclinically ascertained twins, concordance for AN was substantially greater in MZ twinpairs 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 concordancerates 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 theEEA in this study inferences regarding the aetiology of AN have not been made from these

38 ELIZABETH WINCHESTER AND DAVID COLLIERresults (Fairburn et al., 1999) The heritability of AN was estimated to be 76% in anotherpopulation-based twin sample (Klump et al., 2001) and 58% in a bivariate analysis of ANand major depression (Wade et al., 2000) The magnitude of the genetic contribution to ANremains unresolved Large-scale twin studies are needed to define the extent and nature ofthe 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 haveconsistently 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 toaccount for the remaining variance in liability to BN The magnitude of the contribution ofshared 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 havebeen shown to be heritable in different populations of twins These continuous traits areassessed 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 twinpopulation (Holland et al., 1988), and in another twin study several EDI subscales showedheritabilities ranging from 28% to 52% (Rutherford et al., 1993) Heritabilities of 46% and70% 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 environmentalinfluences on these traits Marked differences in heritabilities for EDI subscales have beenreported for a preadolescent (aged 11 years) and an adolescent (aged 17 years) twin samplefrom the same population (Klump et al., 2000) The contribution of additive genetic effectsfor the EDI subscales was greater in the adolescent twin sample than in the preadolescentgroup 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 betweeneating disorders and personality traits and other psychiatric disorders Family studies in-vestigating the relationship between personality traits and eating disorders have shown thatsome personality traits are significantly elevated in the unaffected relatives of probandswith 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 probandscompared 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 traitsresults from the sharing of common genetic risk factors Results from twin studies suggestthat 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 effectsinfluencing eating disorders that are independent of those contributing to the personalitytraits 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 eatingdisorders The development of eating disorders is likely to involve interactions betweenmultiple 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 thesestudies estimates of heritability vary, and thus the relative importance of genetic factors inthe causation of obesity remain controversial

Obesity shows strong familial aggregation but, except for rare monogenic forms of sity, it does not exhibit a clear pattern of Mendelian inheritance Many family studies haveshown that the risk of obesity (BMI> 30) is higher in the biological relatives of obese indi-

obe-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 inobesity 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 onBMI 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 phenotypicvariation, and interacts with other genes and environmental factors Each gene variant isneither 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 lations and between different groups within populations are closely associated with socio-economic and behavioural factors (Sorensen & Echwald, 2001) The rising epidemic ofobesity throughout the western world and developing countries cannot be explained by

popu-40 ELIZABETH WINCHESTER AND DAVID COLLIERrecent 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 toobesity is mainly determined by genetic factors but a favourable environment is necessaryfor 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 geneticsusceptibility would be amplified in a high-risk environment Based on this model the risingprevalence 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 PimaIndians living in the USA who have a much higher prevalence of obesity and type 2 diabetesthan the Pima Indians living in Mexico, where food availability is restricted (Ravussin &Bouchard, 2000) There has been much speculation over why the human genome containsgenetic variants that predispose to obesity One explanation is the ‘thrifty genotype hypoth-esis’ (Neel, 1962) This hypothesis suggests that evolution through alternating periods offamine with periods of food abundance positively selected for genetic variants that confersurvival advantages in famine periods, e.g ‘thrifty genes’ (Ravussin & Bouchard, 2000).These ‘thrifty genes’ are deleterious in modern western societies where calorie-rich foodsare abundant

MOLECULAR GENETIC METHODOLOGY FOR IDENTIFYING SUSCEPTIBILITY GENES FOR COMPLEX DISEASES

Two convergent approaches are used to identify gene variants contributing to the bility of complex diseases: linkage and association studies Candidate genes for a complextrait 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 complexdisorder can be examined in targeted linkage studies and/or association studies

suscepti-Linkage Studies

Non-parametric (‘model-free’) methods of linkage analysis are used for complex traitsbecause this method does not require prior knowledge about the inheritance of a disease Innon-parametric linkage analysis the segregation of variants of anonymous, highly variabledeoxyribonucleic acid (DNA) loci (marker alleles) is examined in affected family memberpairs, e.g affected sister pairs Marker alleles shared by affected relative pairs more oftenthan would be expected by chance provide evidence that there is a linkage between themarker and the disease under investigation, which can either be a dichotomous complextrait 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, whichare 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 significanceminimizes 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 throughoutthe genome are examined in affected relative pairs The DNA markers with significantlinkages identify novel candidate chromosomal regions (susceptibility loci) that may en-compass unknown or unexpected susceptibility genes Quantitative trait loci (QTL), whichare 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 extremescores on a measure of a quantitative trait QTL linkage analysis is a powerful approachfor 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 geneticvariants

In targeted sib-pair linkage studies the segregation of a genetic variant of a candidategene 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 Bothdesigns 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 acontrol group from the same population An allele, which is either directly involved inthe genetic susceptibility of a disease, or closely linked to the causative allele, will occurmore often in cases than in controls than would be expected by chance The differences inallele frequencies between cases and controls are tested for statistical significance using astatistical measure such as the chi-squared or odds ratio test The risk of false positive orfalse 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 wherethe cases and controls may consist of genetically distinct subsets, e.g different ethnicgroups (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 Infamily-based (family trios) association studies the alleles that the parents do not pass ontotheir 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 candidategenes are not excluded on the basis of negative findings and that positive associations arereplicated 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 onphenotypic variance

CHOOSING THE PHENOTYPE FOR MOLECULAR

GENETIC STUDIES

The definition of the phenotype or the diagnostic criteria used to classify individuals asaffected or unaffected is an important consideration when designing molecular genetic

42 ELIZABETH WINCHESTER AND DAVID COLLIERresearch strategies for complex diseases It is important that the diagnostic criteria used ingenetic studies are robust and reliable, so that results from different studies are comparable.

be-‘partial syndromes’ It has been proposed that it might be more appropriate to view all eatingdisorders 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 differencesbetween eating disorder categories, such as between BN and obesity, may be quantitativerather than qualitative

Several of the personality traits and Axis II disorders that are frequently associated witheating disorders have been shown to precede the development of eating disorders and topersist 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 shouldnot only be classified in terms of eating symptoms but also by personality types Threepersonality domains have been identified: a high functioning, self-critical, perfectionisticgroup, which was mainly associated with BN; a constricted, overcontrolled group restrictingpleasure, needs, emotions, relationships and self-knowledge, which was associated withRAN; and an impulsive, undercontrolled and emotionally dysregulated group (Goldner

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 statisticalpower of genetic studies (Barsh et al., 2000) There are several different measures of obesityand related phenotypes The most widely used measure of general obesity is the body massindex (BMI), which is defined as the weight in kilograms (kg) divided by body area Inpractice the BMI is usually estimated by dividing the weight (kg) by the height squared (m2).This measure is reliable, inexpensive and convenient for large sample numbers, however itdoes not account for the proportion of fat to muscle mass in the body and is influenced byfactors 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 moreaccurate measure of obesity and can be assessed from underwater weighing or bioelectricalimpedance The amount of subcutaneous fat distribution can be assessed by the sum ofskinfold thickness measured at different sites around the body or various skinfold ratios(Perusse & Chagnon, 1997) Abdominal obesity is measured using the ratio of waist tohip circumference (WHR) and waist circumference, which is the best correlate of visceralfat (Despres et al., 2001) Intermediary phenotypes, which relate more to the underlyingphysiology 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 moleculargenetic studies The different obesity-related phenotypes are likely to have unique andshared genetic risk factors

The heritable personality traits often associated with eating disorders and other eatingdisorder 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 Multiplequantitative phenotypes can be analysed to increase the statistical power of linkage andassociation studies However, multiple comparisons will be necessary, which raises thethreshold required to achieve statistical significance and this will result in a reduction inpower

IDENTIFICATION OF SUSCEPTIBILITY GENES FOR EATING

DISORDERS AND OBESITY

Genetic research into eating disorders is in its infancy and to date only one genome-widelinkage study has been completed for eating disorders, the results of which have not yet beenpublished However, other genome-wide linkage studies in large populations are currentlyunderway Several candidate gene association studies have been completed, but the majorityhave reported negative findings

Two approaches have been adopted in obesity research: one has studied the rare gene (monogenic) mutations causing obesity in rodents and in humans, and the other hasstudied the genetics of common variation in body weight Identification of some of the genesresponsible for Mendelian forms of obesity in rodents and humans has directly resulted

single-in the unravellsingle-ing of a fundamental pathway single-involved single-in body weight regulation (Barsh

et al.,2001) In the effort to identify genetic variants contributing to common obesity, QTLhave been mapped in human populations and in polygenic animal models of obesity and

44 ELIZABETH WINCHESTER AND DAVID COLLIERmany candidate genes have been evaluated in linkage and association studies A forumknown as the ‘Human Obesity Gene Map’ has been established, in which the results fromall the published studies on the genetics of obesity are collected with the aim of helping toguide the design of future studies (Perusse et al., 2001).

Remarkable progress has been made over the last decade in understanding the geneticmechanisms underlying human body weight regulation (Barsh et al., 2000) As a result ofthese 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 andexpenditure This section will summarize:

rThe monogenic causes of obesity in rodents and humans

rThe association and linkage results for the genes involved in body weight regulatorypathways

rOther candidate genes for eating disorders

rOther candidate genes for obesity

rObesity QTL identified in human populations through genome-wide linkage studies and

in polygenic animal models of obesity

rThe search for lean genes.

Mongenic Rodent Models of Obesity

The genes responsible for six naturally occurring single-gene (monogenic) mutation mousemodels 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 ProteinMouse Mouse Human location in product of

Diabetes (db) Lepr LEPR 1p31 Leptin receptor Chen et al (1996)Agouti

Tubby (tub) Tub TUB 11p15.5 Insulin-signalling

protein

Kleyn et al (1996);Kapeller (et al.)1999

Mahogany

(mg)

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 inthese 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 damental endocrine feedback loop regulating the size of adipose (fat) tissue mass, known asthe leptinergic–melanocortinergic system, that is conserved among all mammals (reviewed

fun-in chapters fun-in this handbook and fun-in Spiegelman and Flier, 2001) Leptfun-in, which is expressed

in adipose tissue and circulates in proportion to adipose tissue mass, serves as the ent signal of this loop informing the brain about the status of the body’s fat stores It actsthrough leptin receptors on nerve cells in the arcuate nucleus of the hypothalamus to triggerneuropeptide responses that modulate appetite and energy expenditure

affer-Through identification of the other rodent obesity genes, knockout and transgenic micestudies 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 relatedtranscript (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 logical roles.α-MSH reduces food intake and increases energy expenditure through acti-

physio-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 ygeneproduct—the agouti coat-colour protein—in the brain where it mimics AgRP by antagoniz-ing the signalling ofα-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 ymice, therebysupporting 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

46 ELIZABETH WINCHESTER AND DAVID COLLIER

(mg) mutation and is involved in suppressing diet-induced obesity (Nagle et al., 1999; Gunn

et al., 1999)

Targeted gene-deletion studies in rodents have identified the components that act stream of the melanocortin signal, additional components that interact with leptin andother neuropeptide pathways that either stimulate or inhibit feeding Two examples are theorexigenic neuropeptide melanin-concentrating hormone (MCH) (Ludwig et al., 2001) and

down-the serotonin IIC receptor (Htr-2c) (Barsh et al., 2000) A description of down-these is beyond

the scope of this chapter but has been reviewed by Inui (2000) and Spiegelman and Flier(2001) The genes encoding these components provide candidate genes for human obesityand targets for therapeutic intervention

Monogenic Human Obesity Syndromes

To date, 19 loss of function mutations in six different genes have been found to be the cause

of 47 cases of monogenic forms of human obesity (Perusse et al., 2001) Mutations in the

LEP (Montague et al., 1997; Strobel et al., 1998), LEPR (Clement et al., 1998), MC4R (Vaisse et al., 1998; Yeo et al., 1998; Hinney et al., 1999), and POMC (Krude et al., 1998)

genes have been reported in 45 human obesity cases

The obesity phenotypes in mice and in humans with homologous mutations are verysimilar, confirming the fundamental nature of the leptinergic–melanocortinergic signallingpathway in the regulation of body weight among mammals However, important species-specific differences in energy physiology have also been defined; in particular there aredifferences in the metabolic and endocrinological phenotypes caused by leptin signallingdefects in humans and mice (Barsh et al., 2000)

A loss of function mutation in the prohormone convertase 1 (PC1) gene has been found

as the cause of an obesity syndrome in one three-year-old case (Jackson et al., 1997) Thisobesity syndrome is very similar to the mouse Fat obesity syndrome caused by mutations

in Cpe Although Cpe and PC1 are non-homologous genes they have similar functions and

are both involved in processing prohormones, in particular POMC (Barsh et al., 2000) A

loss of function mutation in the single-minded (Drosophila) homolog 1 (SIM1) gene is the most probable cause of obesity in a six-year old case (Holder et al., 2000) In mice the Sim1

gene is a critical transcription factor for the formation of the paraventricular nuclei in thehypothalamus, which are known to be involved in energy homeostasis (Holder et al., 2000)

MC4R mutations are the most common cause of monogenic human obesity, with 11

mutations responsible for 34 out of the 47 reported cases of obesity with known mutations(Perusse et al., 2001) Several of the mutations appear to influence the function of the

gene Obesity status appears to differ between individuals with MC4R mutations and not

all individuals with these mutations are obese, which suggests that these mutations showvariable penetrance (Vaisse et al., 2000)

Overall the mutations identified in these six genes are very rare, which suggests that theyare not responsible for the most common forms of obesity in the population However, otherless harmful variants of these genes may influence common human obesity and the resultsfrom linkage and association studies with other variants of these genes are discussed later

in this chapter

There are currently over 26 Mendelian human disorders in which obesity is one ofseveral symptoms (Perusse et al., 2001) The genetic location for 24 of these syndromes

GENETIC AETIOLOGY OF EATING DISORDERS AND OBESITY 47have been mapped including Prader–Willi, Alstrom, Bardet-Biedl and Cohen syndromes(Perusse et al., 2001) For some of these syndromes candidate genes have been identifiedwithin the genetic location and implicated in causation (Perusse et al., 2001) Althoughthese rare obesity-related Mendelian disorders are distinct from common forms of obesity,identification of the underlying mutant genes may provide candidate genes for extremehuman obesity and/or information on the regulation of food intake and energy expenditure.

To date many of the known chromosomal regions have not shown significant linkage tocommon obesity in genome-wide or in targeted linkage studies

Candidate Gene Analyses for Eating Disorders and Obesity

Genes Involved in Body Weight Regulatory Pathways

Leptin–Melanocortinergic System

Genetic variants of genes encoding components of the leptin–melanocortinergic systemhave been tested for association with the eating disorders and obesity (see Table 3.2) Thefinding that disturbances in weight regulation pathways persist after long-term recovery of

AN suggest that these disturbances could be involved in the aetiology of AN (Hinney et al.,2000) However, to date no association between genetic variants of these genes and AN

or BN has been reported (Hinney et al., 2000) Some of these negative findings may befalse negatives due to the use of small sample sizes or the use of an inappropriate controlgroup in some of the studies (Hinney et al., 2000) Alternatively the negative findings couldindicate that these variants do not have a significant role in the genetic predisposition toeating disorders

In contrast variants of the LEP (Butler et al., 1998; Hager et al., 1998b; Li et al., 1999; Mammes et al., 1998; Oksanen et al., 1997), LEPR (Chagnon et al., 2000b; Mammes et al., 2001; Roth et al., 1998), MC4R (Chagnon et al., 1997b), and POMC (Hixson et al., 1999)

genes have been significantly associated with obesity and obesity-related phenotypes (seeTable 3.2) Linkage studies have also reported strong evidence for linkage between variants

of these genes and obesity and obesity-related phenotypes (Chagnon et al., 1997b, 1999;Clement et al., 1996; Duggirula et al., 1996; Lapsys et al., 1997; Ohman et al., 1999; Reed

et al., 1996; Roth et al., 1997; Rutkowski et al., 1998) Variants of the NPY gene have been

associated with birth weight (Karvonen et al., 2000), and BMI (Bray et al., 2000) Obesity

in Pima Indians was associated with a variant in the NPY receptor Y5 gene (NPY5R)

(Jenkinson et al., 2000)

Serotonergic and Dopaminergic Neurotransmitter Systems

The serotonergic and dopaminergic neurotransmitter systems are involved in central energybalance pathways (Spiegelman & Flier, 2001) Serotonergic signalling suppresses foodintake The serotonin and leptin pathways can converge since leptin has been shown toincrease serotonin turnover.Disturbances in the serotonergic and neurotransmitter systemsoccur in individuals with AN and BN and appear to persist after recovery (Hinney et al.,2000) Individuals with eating disorders exhibit multiple neuroendocrine and neuropep-tide disturbances, the majority of which are secondary to malnutrition and/or weight loss

50 ELIZABETH WINCHESTER AND DAVID COLLIER(Kaye et al., 2000a) Serotonergic neurotransmission appears to remain increased in long-term weight-restored AN and BN patients suggesting that serotonergic dysfunction might

be a premorbid trait that contributes to the susceptibility of eating disorders (Kaye et al.,2000a) Serotonin (5-hydroxytryptamine; 5-HT) is involved in a range of physiologicaland behavioural functions including mood and sex drive Serotonergic dysfunction couldtherefore also contribute to other eating disorder symptoms Increased brain 5-HT activityhas been associated with several of the personality traits that appear to occur premorbidly

in some eating disorder patients, such as perfectionism, obsessiveness and rigidity (Hinney

et al., 2000) The serotonergic system includes serotonin, tryptophan hydroxylase, the 5-HTtransporter (SERT) and several 5-HT receptors A variant of the 5-HT transporter gene wasnot associated with AN in three studies but showed a positive association with BN in onestudy (Di Bella et al., 2000; Hinney et al., 1997a; Sundaramurthy et al., 2000)—see Table 3.2

A 5-HT transporter gene variant has also been associated with specific personality traits(Ebstein et al., 2000) Inconsistent findings have been reported for a variant (-1438 G/A) of

the 5-HT 2a receptor gene and AN Four studies in different population groups reported an

increase in the A-allele of the 5-HT 2a variant in AN women compared to controls (Collier

et al., 1997; Enoch et al., 1998; Nacmias et al., 1999; Sorbi et al., 1998) However threestudies could not replicate this positive association (Campbell et al., 1998; Hinney et al.,1997b; Ziegler et al., 1999)—see Table 3.2 In two of the studies with positive findings theassociation was only found with the restricting type of AN and not the binge–purging type

of AN (Nacmias et al., 1999; Sorbi et al., 1998) Different diagnostic criteria, the use ofheterogeneous populations or small sample sizes may, in part, account for the inconsistentresults from these studies (Hinney et al., 2000) A meta-analysis of all the results detected no

association between AN and the A-allele of this 5-HT 2agene variant (Ziegler et al., 1999).The role of this variant in the aetiology of AN therefore remains to be determined in large-

scale association studies No association has been reported between this 5-HT 2agene variantand BN (Enoch et al., 1998; Nacmias et al., 1999; Ziegler et al., 1999) Tests for association

between other variants of the 5-HT 2a gene and AN and BN have all been non-significant(Hinney et al., 2000)

A genetic variant of the 5-HT 2creceptor gene has been associated with obesity (BMI>28)

(Yuan et al., 2000) and an obesity QTL showing suggestive linkage has been identified onchromosome Xq24, which is the chromosomal location of this receptor (Ohman et al., 2000).Dietary energy and carbohydrate and alcohol intake in obese subjects has been associated

with a variant in the 5-HT 2a receptor gene (Aubert et al., 2000)—see Table 3.2 Thesepositive associations need to be replicated in independent populations Genetic variants of

the dopamine D3 and dopamine D4 receptor genes (DRD3, DRD4) have been tested for

association with AN with consistent negative findings (Bruins-Slot et al., 1998; Hinney et al.,

2000) Genetic variants of the dopamine D2 receptor gene (DRD2) have been significantly

associated with obesity (BMI>30) (Spitz et al., 1999), triceps skinfold (Thomas et al.,

2000), and relative weight (Comings et al.,1993)

GENETIC AETIOLOGY OF EATING DISORDERS AND OBESITY 51

in brown adipose tissue (BAT), UCP-2, which is widely expressed in many tissues, and UCP-3, expressed in BAT and skeletal muscle A positive association between AN and a genetic variant near the uncoupling protein-2/uncoupling protein-3 (UCP-2/UCP-3) gene

cluster has been reported (Campbell et al., 1999)—see Table 3.2 This positive finding needs

to be replicated in an independent sample to confirm its importance Many association ies have reported positive associations between obesity and/or obesity-related phenotypes

stud-and variants of the UCP-1, UCP-2 stud-and UCP-3 genes (Perusse et al., 2001)—see Table 3.2.

Adipose Tissue Metabolism

Beta adrenergic receptors are involved in lipid metabolism by activating lipase, which yses lipolysis A genetic variant of theβ3-adrenergic receptor (ADRβ3) was not associated

catal-with AN or BN (Hinney et al., 1997c) Numerous association and linkage studies have vestigated the role of this genetic variant in common obesity (Perusse et al., 2001) However,the results from these studies are conflicting and the importance of this variant in obesityremains to be determined Obesity and other related phenotypes have been associated withgenetic variants of theβ2-adrenergic receptor (ADRβ2) gene in several independent studies

in-(Perusee et al., 2001)—see Table3.2

Other Candidate Genes for the Eating Disorders

Candidate genes for eating disorders also include those involved in mood, personality andresponses to stress Based on the female predominance of eating disorders and the fre-quent onset around puberty, it has been suggested that an exaggerated sensitivity of thebrain to rising oestrogen levels during puberty, which would have an anorectic effect,may be involved in the development of eating disorders The gene encoding the oestrogen

β-receptor (ERβ) is a candidate gene and the frequency of a variant of this gene was

in-creased in AN cases compared to controls in one association study This positive associationneeds to be independently replicated (Rosenkranz et al., 1998)

Animal models of eating disorders could provide other plausible candidate genes There

is one spontaneous mouse model of AN, which is caused by a lethal autosomal recessive

mutation on mouse chromosome 2 (Son et al., 1994) This anorexia (anx) mutation is

associated with marked alterations in many of the known hypothalamic neuropeptides

involved in appetite control The anx/anx mouse is a useful model for exploring the role of

the hypothalamus in the regulation of food intake and for identifying new therapeutic targets

for AN The anx gene and its product(s) have not been identified so far but elucidation of this

gene will aid in furthering the understanding of appetite control The selective breeding forleanness in agricultural farm animals has uncovered recessive mutations causing syndromesrelated to AN, for example thin sow syndrome These syndromes could provide valuablemodels of AN (Treasure & Owen, 1997)

Other Candidate Genes for Obesity

Many other genes have been tested for association with obesity and obesity-related notypes including genes encoding the apolipoproteins (APO), which are involved in lipid

phe-52 ELIZABETH WINCHESTER AND DAVID COLLIERmetabolism, genes involved in adipocyte differentiation such as the peroxisome proliferator-

activated receptor (PPAR) genes, and the glucocorticoid receptor (GRL) gene involved in

the hypothalamus–pituitary–adrenal (HPA) axis, which is abnormally regulated in obesity(Rosmond et al., 2001) The list of candidate genes for obesity is vast and the task forresearchers is to prioritize the most plausible genes for genetic research

To date 48 candidate genes have shown significant associations with obesity and related phenotypes (Perusse et al., 2001) Several of the positive associations have beenreplicated in independent populations However it is important to note that the majority ofthe candidate genes showing positive associations have also shown non-significant associ-ations in different studies The disparity between different studies may, in part, be due tothe methodological limitations of association studies mentioned earlier in this chapter ormay reflect differences in genetic background The formidable task of identifying the truepositive associations from the growing list of significant associations remains In addition,the variants of the candidate genes that have shown positive associations have not beenfound to affect the function of the gene products and therefore the causative variants towhich they are linked need to be identified

obesity-Human Genome-Wide Linkage Studies for Obesity—Identification

Table 3.3 Summary of some human QTL showing strong and suggestive evidence of

linkage to obesity and obesity-related phenotypes

location of QTL Obesity phenotype p-value References

2p21 Leptin, fat mass, BMI Lod= 4.9/2.8 Comuzzie et al (1997)

0.008 < p < 0.03 Rotimi et al (1999)20q13 BMI>30, %fat 3.0< Lod < 3.2 Lee et al (1999)

10p11.22 Obesity 1.1< Lod < 2.5 Hinney et al (2000)

aFor whole genome-wide linkage analyses a lod score>3.3 is considered statistically significant evidence for the

presence of linkage.

[For a full list of the human obesity QTL see the latest update of the Human Obesity Gene Map (Perusse et al.,

2001).

GENETIC AETIOLOGY OF EATING DISORDERS AND OBESITY 53independent populations should eliminate false positive results and confirm the potentialimportance of a QTL However, the majority of QTL identified to date have not beenreplicated A possible explanation for this is that the genetic variants underlying variation

in obesity and related phenotypes differ across populations

Evidence supporting some QTL is very convincing The strongest QTL are shown inTable 3.3 A strong QTL on the short arm (p) of chromosome 2 at band 21 (2p21) influencingserum leptin levels has been identified Evidence for linkage of this locus to serum leptinlevels was first reported in a genome-wide linkage study in Mexican-Americans (Comuzzie

et al., 1997), and was later replicated in two independent studies, one of French sibling pairs(Hager et al., 1998a) and the other in an African-American population (Rotimi et al., 1999).Replication of this linkage result in different populations provides convincing evidence that2p21 is an important obesity-related locus This chromosomal region encompasses several

potential candidate genes including the glucokinase regulatory protein (GCKR) and POMC genes (Comuzzie et al., 1997) Common variants of the POMC gene have been associated

with normal variation in leptin levels (Hixson et al., 1999)

The chromosomal region, 20q11–q13, has been implicated in human obesity in severallinkage studies in humans and in mice (Perusse et al., 2001) In a genome-wide linkage study

in an American population BMI (>30) and % fat showed evidence for linkage with 20q13

markers (Lee et al., 1999) In a targeted linkage study BMI, fat mass and the sum of six

skinfolds showed evidence of linkage to the MC3R gene located at 20q13.2–q13.3 and to the adenosine deaminase (ADA) gene located at 20q12–q13 (Lambertas et al., 1997) Suggestive

evidence for linkage between the 24-hour respiratory quotient (RQ) and a marker at 20q11.2was reported in a genome-wide screen in Pima Indians (Norman et al., 1998) A mouseobesity QTL has been identified on mouse chromosome 2, a region syntenic to chromosome20q (Lembertas et al., 1997; Mehrabian et al., 1998) Thus the evidence supporting a role for

chromosome 20q11–q13 in human obesity is convincing In addition to ADA and MC3R, this region contains other plausible candidate genes such as the agouti-signalling protein (ASIP) gene and the CAAT/enhancer-binding protein beta (CEBPβ) gene (Lee et al., 1999) Also the hepatic nuclear factor gene (4HNF4), which when mutated causes one form of maturity

onset diabetes of the young (MODY1) is located in 20q12 and two susceptibility loci fornon-insulin-dependent diabetes (NIDDM) have been localized to 20q (Lee et al., 1999).There is evidence from two genome-wide screens in different populations, for a majorsusceptibility locus for obesity on chromosome 10p (Hager et al., 1998a; Hinney et al.,2000) However, this region does not contain any obvious candidate genes for obesity

Identification of QTL in Polygenic Animal Models of Obesity

QTL analysis in polygenic animal models of obesity is relatively easier than in humansand, to date, 115 QTL linked to body weight or body fat have been reported from cross-breeding experiments in various animals (Perusse et al., 2001) Laboratory animals areideal model systems for QTL analysis because the effects of environmental factors andgenetic background can be held constant and specific phenotypes such as adiposity orenergy expenditure can be selected for over many generations (Barsh et al., 2000)

A highly dense and reliable mouse gene map for polygenic obesity has been generated(Perusse et al., 2001) On the basis of synteny between the mouse and human genomes, themouse obesity QTL have been mapped to their putative homologous locations in the human

54 ELIZABETH WINCHESTER AND DAVID COLLIERgenome (Perusse et al., 2001) The search for the causative gene variants underlying themouse QTL and candidate genes within the homologous chromosomal regions in humans

is currently underway Some of the mouse QTL have mapped to human genomic regions

containing known candidate genes such as the UCP-1, UCP-2 and UCP-3 genes (Echwald,

1999)

QTL analysis in polygenic animal models of obesity offers the opportunity to investigatespecific questions related to human obesity such as the role of genetic factors in determiningthe response of body fat composition to changes in dietary fat intake (Perusse & Bouchard,2000) Mouse models of diet-induced obesity provide the most promising approach of iden-tifying the genes responsible for modulating the response to diet Three QTL determiningthe response to dietary lipids in a mouse model of diet-induced obesity have been identifiedand mapped to their syntenic regions in the human genome, chromosomes 1, 3 and 8 (West

et al., 1994) Suggestive evidence of linkage has been reported between human chromosome

1 markers and various obesity phenotypes (Chagnon et al., 1997a)

The Search for Lean Genes

An alternative approach to understanding the genetic basis of eating disorders and sity might be to search for genes involved in the control of body leanness (fat free mass)(Bjorntorp, 2001) Fat free mass (FFM) consists mostly of bone tissues and skeletal mus-cle and can be calculated from percent body fat A genome-wide linkage study has beenconducted to identify candidate chromosomal regions for FFM In this study FFM showedsignificant linkage to a genetic marker within the insulin-like growth factor-1 receptor

obe-(IGF-1R) gene on chromosome 15q25–q26 and to two markers on chromosome 18q12

(Chagnon et al., 2000a) A moderately significant linkage was observed on chromosome7p15.3, which contains a plausible candidate gene, the growth hormone-releasing hormone

(GHRH) receptor gene These positive linkages need to be replicated in other populations.

An association between a variant of the insulin-like growth factor-1 (IGF-1) gene and FFM has been reported (Sun et al., 1999) This IGF-1 gene variant has also been linked to the

changes in FFM in response to 20 weeks of endurance exercise (Sun et al., 1999) The roles

of variants of the IGF-1R, GHRH, IGF-1 genes in eating disorders and obesity need to be

assessed in association studies

Another approach to identify lean genes is to examine genetic variants in people thathave managed to keep their bodyweight constant without difficulty These people are a rare,specific subgroup who might have genetic variants that differ from the general populationand that are protecting them from gaining weight In a study of women who have managed

to keep their weight constant from the age of 21 years, a specific variant of the aromatasegene, whose protein product functions more efficiently, has been implicated in their ability

to stay lean (Bjorntorp, 2001) The identification of such genes may provide targets fortherapeutic intervention in obesity

CONCLUSION

Thus far, there has been little success in elucidating the polygenic component to the aetiology

of either eating disorders or common human obesity

GENETIC AETIOLOGY OF EATING DISORDERS AND OBESITY 55The majority of candidate gene association studies for eating disorders have reportednegative findings It is impossible to draw conclusions from these results because many ofthe studies were small and used heterogeneous populations There have been a few positiveassociations but these need to be replicated in independent populations to confirm their

importance The 5-HT 2agene is a plausible candidate but its role in the genetic aetiology of

AN remains unresolved It is hoped that the large-scale association and linkage studies thatare currently underway will have greater statistical power to detect small genetic effectsand lead to the identification of susceptibility genes for eating disorders

To date, over 250 candidate genes, markers, or chromosomal regions have been linked

or associated with common human obesity phenotypes and this number will continue toexpand over the coming years (Perusse et al., 2001) These putative obesity loci have beenfound on all human chromosomes except the Y chromosome Despite the number of putativeobesity loci there are as yet no common obesity susceptibility genes Identification of thetrue obesity loci and the causative genetic variants is a formidable task

Genetic studies in monogenic and polygenic animal models of obesity have providedvaluable insight into fundamental pathways regulating appetite and energy expenditure.The number of mouse obesity genes and QTL will continue to increase over the comingyears, and this will aid in the identification of new pathways involved in energy homeostasis,additional components of already identified pathways and guide candidate gene analyses

in human studies

A fundamental flaw in current research strategies can in part explain the lack of success

in identifying susceptibility genes for these disorders Current approaches investigate therelationship between a variant in a single gene and a phenotype/disease without controllingfor gene–gene interactions and/or environmental factors, neither of which have been clearlydefined (Sorensen & Echwald, 2001) Some genetic variants may only show an effect incombination with other gene variants or environmental factors Polygenic animal modelsoffer the opportunity to explore gene–gene interactions and gene–environment interactions.Another problem is that the sample sizes needed to detect genes of truly small effects areunrealistically large for an individual researcher to collect (Comuzzie & Allison, 1998).More powerful approaches of detecting genes of small effect are being developed, such aswhole-genome association studies (Kruglyak, 1999)

The challenge for future research is to determine the combination of genetic variants andepistatic (gene–gene) interactions that contribute to the aetiology of eating disorders andobesity and the environmental circumstances in which the genetic predisposition is fullyexpressed (Perusse et al., 2001) It is hoped that progress in understanding the genetic basis

of these disorders will provide the basis for more rational pharmacological treatment and/orpreventative therapeutic strategies for eating disorders and obesity

REFERENCES

APA, (1994) Diagnostic and Statistical Manual of Mental Disorders (4th Edition) Washington, D.C.:

American Psychiatric Association

Aubert, R., Betoulle, D., Herbeth, B., Siest, G & Fumeron, F (2000) 5-HT2A receptor gene

poly-morphism is associated with food and alcohol intake in obese people Int J Obes Relat Metab.

Disord., 24, 920–924.

Barsh, G.S., Farooqui, I.S & O’Rahilly, S (2000) Genetics of body-weight regulation Nature, 404,

644–651

56 ELIZABETH WINCHESTER AND DAVID COLLIER

Bjorntorp, P (2001) Thrifty genes and human obesity: Are we chasing ghosts? Lancet, 358, 1006–

1008

Bray, M.S., Boerwinkle, E & Hanis, C.L (2000) Sequence variation within the neuropeptide Y gene

and obesity in Mexican Americans Obes Res., 8, 219–226.

Bruins-Slot, L., Gorwood, P., Bouvard, M., Blot, P., Ades, J., Feingold, J., Schwartz, J.C & Simeoni, M.C (1998) Lack of association between anorexia nervosa and D3 dopamine receptor

Mouren-gene Biol Psychiat., 43, 76–78.

Bulik, C.M., Sullivan, P.F., Wade, T.D & Kendler, K.S (2000) Twin sudies of eating disorders: A

review Int J Eat Disord., 27, 1–20.

Bulik, C.M., Sullivan, P.F & Kendler, K.S (1998) Heritability of binge-eating and broadly defined

bulimia nervosa Biol Psychiat., 44, 1210–1218.

Butler, M.G., Hedges, L., Hovis, C.L & Feurer, I.D (1998) Genetic variants of the human obesity(OB) gene in subjects with and without Prader-Willi Syndrome: comparison with body mass index

and weight Clin Genet., 54, 385–393.

Campbell, D.A., Sundaramurthy, D., Gordon, D., Markham, A.F & Pieri, L.F (1999) Associationbetween a marker in the UCP-2/UCP-3 gene cluster and genetic susceptibility to anorexia nervosa

the fat-free body mass in the Quebec family study Metabolism, 49, 203–207.

Chagnon, Y.C., Wilmore, J.H., Borecki, I.B., Gagnon, J., Perusse, L., Chagnon, M., Collier, G.R.,Leon, A.S., Skinner, J.S., Rao, D.C & Bouchard, C (2000b) Associations between the leptinreceptor gene and adiposity in middle-aged caucasian males from the HERITAGE family study

J Clin Endoc Metab., 85, 29–34.

Chagnon, Y.C., Chung, W.K., Perusse, L., Chagnon, M., Leibel, R.L & Bouchard, C (1999) Linkagesand associations between the leptin receptor (LEPR) gene and human body composition in the

Quebec family study Int J Obes Relat Metab Disord., 23, 278–286.

Chagnon, Y.C., Perusse, L., Lamothe, M., Chagnon, M., Nadeau, A., Dionne, F.T., Gagnon, J., Chung,W.K., Leibel, R.L & Bouchard, C (1997a) Suggestive linkages between markers on human 1p32-

22 and body fat and insulin levels in the Quebec family study Obes Res., 5, 115–121.

Chagnon, Y.C., Chen, W.J., Perusse, L., Chagnon, M., Nadeau, A., Wilkison, W.O & Bouchard, C.(1997b) Linkage and association studies between the melanocortin receptors 4 and 5 genes and

obesity-related phenotypes in the Quebec Family study Molec Med., 3, 663–673.

Chen, H., Charlat, O., Tartaglia, L.A., Woolf, E.A., Weng, X., Ellis, S.J., Lakey, N.D., Culpepper, J.,Moore, K.J., Breitbart, R.E., Duyk, G.M., Tepper, R.I & Morgenstern, J.P (1996) Evidence thatthe diabetes gene encodes the lepton receptor: identification of a mutation in the leptin receptor

gene in db/db mice Cell 84, 491–495.

Chen, A., Marsh, D.J., Trumbauer, M.E., Frazier, E.G., Guan, X.M., Yu, H., Rosenblum, C.I., Vongs,A., Feng, Y., Cao, L., Metzger, J.M., Strack, A.M., Camacho, R.E., Mellin, T.N., Nunes, C.N.,Min, W., Fisher, J., Gopal-Truter, S., MacIntyre, D.E., Chen, H.Y & Van der Ploeg, L.H.T (2000)Inactivation of the mouse melanocortin-3 receptor results in increased fat mass and reduced lean

body mass Nat Genet., 26, 97–101.

Clement, K., Vaisse, C., Lahlou, N., Cabrol, S., Pelloux, V., Cassuto, D., Gourmelen, M., Dina, C.,Chambaz, J., Lacorte, J.M., Basdevant, A., Bougneres, P., Lebouc, Y., Froguel, P & Guy-Grand,

B (1998) A mutation in the human leptin receptor gene causes obesity and pituitary dysfunction

Nature, 392, 398–401.

Clement, K., Garner, C., Hager, J., Philippi, A., LeDuc, C., Carey, A., Harris, T.J., Jury, C., Cardon,L.R., Basdevant, A., Demenais, F., Guy-Grand, B., North, M & Froguel, P (1996) Indication for

linkage of the human OB gene region with extreme obesity Diabetes, 45, 686–690.

Collier, D.A., Arranz, M.J., Li, T., Mupita, D., Brown, N & Treasure, J (1997) Association between5-HT2agene promoter polymorphism and anorexia nervosa Lancet, 350, 412.

Comings, D.E., Flanagan, S.D., Dietz, G., Muhleman, D., Knell, E & Gysin, R (1993) The dopamine

D2 receptor (DRD2) as a major gene in obesity and height Biochem Med metab Biol., 50, 176–

185

GENETIC AETIOLOGY OF EATING DISORDERS AND OBESITY 57

Comuzzie, A & Allison, D (1998) The search for human obesity genes Science, 280, 1347–1378.

Comuzzie, A.G., Hixson, J.E., Almasy, L., Mitchell, B.D., Mahaney, M.C., Dyer, T.D., Stern, M.P.,MacCluer, J.W & Blangero, J (1997) A major quantitative trait locus determining serum leptin

levels and fat mass is located on human chromosome 2 Nat Genet., 15, 273–275.

Despres, J.P., Lemieux, I & Prud’homme D (2001) Treatment of obesity: Need to focus on high risk

abdominally obese patients BMJ, 322, 716–720.

Di Bella, D., Catalano, M., Cavallini, M.C., Riboldi, C & Bellodi, L (2000) Serotonin transporter

linked polymorphic region in anorexia nervosa and bulimia nervosa Molec Psychiat., 5, 233–234.

Duggirula, R., Stern, M.P., Mitchell, B.D., Reinhart, L.J., Shipman, P.A., Uresandi, O.C., Chung,W.K., Leibel, R.L., Hales, C.N., O’Connell, P & Blangero, J (1996) Quantitative variation inobesity-related traits and insulin precursors linked to the OB gene region on human chromosome

7, Am J Hum Genet., 59, 694–703.

Ebstein, R.P., Benjamin, J & Belmaker, R.H (2000) Personality and polymorphisms of genes involved

in aminergic neurotansmission EJP, 410, 205–214.

Echwald, S.M (1999) Genetics of human obesity: Lessons from mouse models and candidate genes

J Int Med., 245, 653–666.

Enoch, M.A., Kaye, W.H., Rotondo, A., Greenberg, B.D., Murphy, D.L & Goldman, D (1998)5-HT2a promoter polymorphism—1438 G/A, anorexia nervosa, and obsessive-compulsive

disorder Lancet, 351, 1785–1786.

Fairburn, C.G., Cowen, P.J & Harrison, P.J (1999) Twin studies and the aetiology of eating disorders

Int J Eat Disord., 26, 349–358.

Fairburn, C.G., & Cooper, Z (1993) The eating Disorders Examination In C Fairburn & G Wilson

(Eds), Binge-eating: Nature, Assessment and Treatment (12th edn; pp 317–360) New York:

Guilford Press

Fichter, M.M & Noegal, R (1990) Concordance for bulimia nervosa in twins Int J Disord., 9,

255–263

Garner, D., Olmsted, M & Polivy, J (1984) Eating Disorders Inventory Manual New York:

Psycho-logical Assessment Resources

Goldner, E.M., Srikameswaran, S., Schroeder, M.L., Livesley, W.J & Birmingham C.L (1999)

Di-mensional assessment of personality pathology in patients with eating disorders Psychiat Res.,

85, 151–159.

Graham, M., Shutter, J.T., Sarmiento, U., Sarosi, I & Stark, K.L (1997) Overexpression of Agrt leads

to obesity in transgenic mice Nat Genet., 17, 273–274.

Gunn, T.M., Miller, K.A., He, L., Hyman, R.W., Davis, R.W., Azarani, A., Schlossman, S.F., Cohan, J.S & Barsh, G.S (1999) The mouse mahagany locus encodes a transmembrane form of

Duke-human attractin Nature, 398, 152–156.

Hager, J., Dina, C., Francke, S., Dubois, S., Hourari, M., Vatin, V., Vaillant, E., Lorentz, N., Basdevant,A., Clement, K., Guy-Grand, B & Froguel, P (1998a) A genome-wide scan for human obsesity

genes reveals a major susceptibility locus on chromosome 10 Nat Genet., 20, 304–308.

Hager, J., Clement, K., Francke, S., Dina, C., Raison, J., Lahlou, N., Rich, N., Pelloux, V., Basdevant,A., Guy-Grand, B., North, M & Froguel, P (1998b) A polymorphism in the 5untranslated region

of the human ob gene is associated with low leptin levels Int J Obes Relat Metab Disord., 22,

200–205

Halaas, J.L., Gajiwala, K.S., Maffei, M., Cohen, S.L., Chait, B.T., Rabinowitz, D., Lallone, R.L.,Burley, S.K & Friedman, J.M (1995) Weight-reducing effects of the plasma protein encoded by

the obese gene Science, 269, 543–546.

Han, L., Nielsen, D.A., Rosenthal, N.E., Jefferson, K., Kaye, W., Murphy, D., Altemus, M., Humphries,J., Cassano, G., Rotondo, A., Virkkunen, M., Linnoila, M & Goldman, D (1999) No coding variant

of the tryptophan hydroxylase gene detected in seasonal affective disorder, obsessive-compulsive

disorder, anorexia nervosa, and alcoholism Biol Psychiat., 45, 615–619.

Hanson, R.L., Ehm, M.G., Pettitt, D.J., Prochazka, M., Thompson, D.B., Timberlake, D., Foroud,T., Kobes, S., Baier, L., Burns, D.K., Almasy, L., Blangero, J., Garvey, W.T., Bennett, P.H &Knowler, W.C (1998) An autosomal genomic scan for loci linked to type II diabetes mellitus and

body-mass index in Pima Indians Am J Hum Genet., 63, 1130–1138.

Hebebrand, J & Remschmidt, H (1995) Anorexia nervosa viewed as an extreme weight condition:

genetic implications Hum Genet., 95, 1–11.

58 ELIZABETH WINCHESTER AND DAVID COLLIER

Hinney, A., Remschmidt, H & Hebebrand, J (2000) Candidate gene polymorphisms in eating

disor-ders EJP, 410, 147–159.

Hinney, A., Schmidt, A., Nottebom, K., Heibult, O., Becker, I., Ziegler, A., Gerber, G., Sina, M.,Gorg, T., Mayer, H., Siegfried, W., Fichter, M., Remschmidt, H & Hebebrand, J (1999) Severalmutations in the melanocortin-4 receptor gene including a nonsense and a frameshift mutation

associated with dominantly inherited obesity in humans J Clin Endoc Metab., 84, 1483–1486.

Hinney, A., Barth, N., Zeigler, A., Von Prittwitz, S., Hamann, A., Hennighausen, K., Lentes,K.U., Heils, A., Rosenkranz, K., Roth, H., Coners, H., Mayer, H., Herzog, W., Siegfried, A.,Lehmkuhl, G., Poustka, F., Schmidt, M.H., Schafer, H., Grzeschik, K.H., Pirke, K.M., Lesch,K.P Remschmidt, H & Hebebrand, J (1997a) Serotonin transporter gene-linked polymorphic

region: Allele distributions in relationship to body weight and in anorexia nervosa Life Sci., 61,

L295–PL303

Hinney, A., Zeigler, A., Nothen, M.M Remschmidt, H & Hebebrand, J (1997b) 5-HT2a receptor

gene polymorphisms, anorexia nervosa and obesity Lancet, 350, 1324–1325.

Hinney, A., Lentes, K.U., Rosenkranz, K., Barth, N., Roth, H., Zeigler, A., Hennighausen, K., Coners,H., Wurmser, H., Jacob, K., Romer, G., Winnekes, U., Mayer, H., Herzog, W., Lehmkuhl, G.,Poutska, F., Schmidt, M.H., Blum, W.F., Pirke, K.M., Schafer, H., Grzeschik, K.H., Remschmidt,H., Hebebrand, J (1997c) Beta 3-adrenergic-receptor allele distributions in children, adolescents

and young adults with obesity, underweight or anorexia nervosa Int J Obes Relat Metab Disord.,

Holder, J.L., Butte, N.F & Zinn, A.R (2000) Profound obesity associated with a balanced translocation

that disrupts the SIM1 gene Hum Molec Genet., 9, 101–108.

Holland, A.J., Sicotte, N & Treasure, J (1988) Anorexia nervosa: Evidence for a genetic basis

J Psychosom Res., 32, 561–571.

Hsu, L.K.G., Chesler, B.E & Santhouse, R (1990) Bulimia nervosa in eleven sets of twins: A clinical

report Int J Eat Disord., 9, 275–282.

Huszar, D., Lynch, C.A., Fairchild-Huntress, V., Dunmore, J.H., Fang, Q., Berkemeier, L.R., Gu, W.,Kesterson, R.A., Boston, B.A., Cone, R.D., Smith, F.J., Campfield, L.A., Burn, P & Lee, F (1997)

Targeted disruption of the melanocortin-4 receptor results in obesity in mice Cell, 88, 131–141.

Inui, A (2000) Transgenic study of energy homeostasis equation: Implications and confounding

influences FASEB Jl, 14, 2158–2170.

Jackson, R.S., Creemers, J.W., Ohagi, S., Raffin-Sanson, M.L., Sanders, L., Montague, C.T., Hutton,J.C & O’Rahilly, S (1997) Obesity and impaired prohormone processing associated with muta-

tions in the prohormone convertase 1 gene Nat Genet., 16, 303–306.

Jenkinson, C.P., Cray, K., Walder, K., Herzog, H., Hanson, R & Ravussin, E (2000) Novel

polymor-phisms in the neuropeptide-Y Y5 receptor associated with obesity in Pima Indians Int J Obes.

Relat Metab Disord., 24, 580–584.

Kapeller, R., Moriarty, A., Strauss, A., Stubdal, H., Theriault, K., Siebert, E., Chickering, T.,Morgenstern, J.P., Tartaglia, L.A & Lillie, J (1999) Tyrosine phosphorylation of tub and its asso-ciation with Src homology 2 domain-containing proteins implicate tub in intracellular signalling

by insulin J Biol Chem., 274, 24980–24986.

Karvonen, M.K., Koulu, M., Pesonen, U et al (2000) Leucine 7 to proline 7 polymorphism in thepreproneuropeptide Y is associated with birth weight and serum triglyceride concentration in

preschool aged children J Clin Endoc Metab., 85, 1455–1460.

Kaye, W.H., Klump, K.L., Frank, G.K.W & Strober, M (2000a) Anorexia and bulimia nervosa Ann.

Rev Med., 51, 299–313.

Kaye, W.H., Lilenfeld, L.R., Wade, H., Berrettini, Strober, M., Devlin, B., Klump, K.L., Goldman, D.,Bulik, C.M., Halmi, K.A., Fichter, M.M., Kaplan, A., Woodside, A.B., Treasure, J., Plotinov, K.,Pollice, C., Radhika, R & McConaha, C.W (2000b) A search for susceptibility loci for anorexia

nervosa: Methods and sample description Biol Psychiat., 47, 794–803.

Kendler, K.S., Walters, E.E., Neale, M.C., Kessler, R.C., Heath, A.C & Eaves, L.J (1995) Thestructure of the genetic and environmental risk factors for six major psychiatric disorders in women:

GENETIC AETIOLOGY OF EATING DISORDERS AND OBESITY 59

Phobis, generalised anxiety disorder, panic disorder, bulimia, major depression, and alcoholism

Arch Gen Psychiat., 52, 374–383.

Kendler, K.S., Maclean, C., Neale, M.C., Kessler, R.C., Heath, A.C & Eaves, L.J (1991) The genetic

epidemiology of bulimia nervosa Am J Psychiat., 148, 1627–1627.

Kleyn, P.W., Fan, W., Kovats, S.G., Lee, J.J., Pulido, J.C., Wu, Y., Berkemeier, L.R., Misumi, D.J.,Holmgren, L., Charlat, O., Woolf, E.A., Tayber, O., Brody, T., Shu, P., Hawkins, F., Kennedy,B., Baldini, L., Ebeling, C., Alperin, G.D., Deeds, J., Lakey, N.D., Culpepper, J., Chen, H.,Glucksmann-Kuis, M.A., Moore, K.J., et al (1996) Identification and characterization of the

mouse obesity gene tubby: A member of a novel gene family Cell, 85, 281–290.

Klump, K.L., Bulik, C.M., Kaye, W.H & Strober, M (2001) The genetics of eating disorders.Manuscript in preparation

Klump, K.L., McGue, M & Iacono, W.G (2000) Age differences in genetic and environmental

influences on eating attitudes and behaviours in preadolescent and adolescent twins J Abnorm.

Psychol., 109, 239–251.

Klump, K.L., Kaye, W.H., Plotinov, K., Pollice, C & Rao R (1999) Familial transmission of ality traits in women with anorexia nervosa and their first-degree relatives Poster presented at theAcademy for Eating Disorders Annual Meeting, San Diego, California

person-Krude, H., Biebermann, H., Luck, W., Horn, R., Brabant, G & Gruters, A (1998) Severe early-onsetobesity, adrenal insufficiency, and red hair pigmentation caused by POMC mutations in humans

Nat Genet., 19, 155–157.

Kruglyak, L (1999) Prospects for whole-genome linkage disequilibrium mapping of common disease

genes Nat Genet., 22, 139–144.

Lambertas, A.V., Perusse, L., Chagnon, Y.C., Fisler, J.S., Warden, C.H., Purcell-Huynh, D.A., Dionne,F.T., Gagnon, J., Nadeau, A., Lusis, A.J & Bouchard, C (1997) Identification of an obesityquantitative trait locus on mouse chromosome 2 and evidence of linkage to body fat and insulin

on the human homologous region 20q J Clin Invest., 100, 1240–1247.

Lander, E & Kruglyak, L (1995) Genetic dissection of complex traits: Guidelines for interpreting

and reporting linkage results Nat Genet., 11, 241–247.

Lapsys, N.M., Furler, S.M., Moore, K.R., Nguyen, T.V., Herzog, H., Howard, G., Samaras, K., Carey,D.G., Morrison, N.A., Eisman, J.A & Chisholm, D.J (1997) Relationship of a novel polymorphic

marker near the human obese (OB) gene to fat mass in healthy woman Obes Res., 5, 430–433.

Lee, J.H., Reed, D.R., Li, W.D., Xu, W., Joo, E.J., Kilker, R.L., Nanthakumar, E., North, M., Sakul,H., Bell., A & Price R (1999) Genome scan for human obesity and linkage to markers in 20q13

Am J Hum Genet., 64, 196–209.

Li, W.D., Reed, D.R., Lee, J.H., Xu, W., Kilker, R.L., Sodam, B.R & Price, R.A (1999) Sequencevariants in the 5 flanking region of the leptin gene are associated with obesity in woman Ann.

leads to obesity and insulin resistance J Clin Invest., 107, 379–386.

Mammes, O., Aubert, R., Betoulle, D., Pean, F., Herberth, B., Visvikis S., Siest G & Fumeron F

(2001) LEPR gene polymorphisms: Associations with overweight, fat mass and response to diet

in women Eur J Clin Invest., 31, 398–404.

Mammes, O., Betoulle, D., Aubert, R., Giraud, V., Tuzet, S., Petiet, A., Colas-Linhart, N & Fumeron,

F (1998) Novel polymorphisms in the 5region of the LEP gene: Association with leptin levels

and response to low-calorie diet in human obesity Diabetes, 47, 487–489.

Mehrabian, M., Wen, P.Z., Fisler, J., Davis, R.C & Lusis, A.J (1998) Genetic loci controlling body

fat, lipoprotein metabolism, and insulin levels in a multifactorial mouse model J Clin Invest.,

101, 2485–2496.

Michaud, E.J., Bultman, S.J., Klebig, M.L., van Vugt, M.J., Stubbs, L.J., Russell, L.B & Woychik,R.P (1994) A molecular model for the genetic and phenotypic characteristics of the mouse lethalyellow (Ay) mutation Proc Natl Acad Sci USA, 91, 2562–2566.