The Human Obesity Gene Map: The 2000 Update


Department of Social and Preventive Medicine, Division of Kinesiology-PEPS Building, Laval University, Sainte-Foy, Québec, G1K 7P4, Canada. E-mail:


This report constitutes the seventh update of the human obesity gene map incorporating published results up to the end of October 2000. Evidence from the rodent and human obesity cases caused by single-gene mutations, Mendelian disorders exhibiting obesity as a clinical feature, quantitative trait loci uncovered in human genome-wide scans and in cross-breeding experiments in various animal models, and association and linkage studies with candidate genes and other markers are reviewed. Forty-seven human cases of obesity caused by single-gene mutations in six different genes have been reported in the literature to date. Twenty-four Mendelian disorders exhibiting obesity as one of their clinical manifestations have now been mapped. The number of different quantitative trait loci reported from animal models currently reaches 115. Attempts to relate DNA sequence variation in specific genes to obesity phenotypes continue to grow, with 130 studies reporting positive associations with 48 candidate genes. Finally, 59 loci have been linked to obesity indicators in genomic scans and other linkage study designs. The obesity gene map reveals that putative loci affecting obesity-related phenotypes can be found on all chromosomes except chromosome Y. A total of 54 new loci have been added to the map in the past 12 months and the number of genes, markers, and chromosomal regions that have been associated or linked with human obesity phenotypes is now above 250. Likewise, the number of negative studies, which are only partially reviewed here, is also on the rise.


This is the seventh update in this series on the status of the human obesity gene map. It incorporates the material published by the end of October 2000. Previous reviews have been published (1) (2) (3) (4) (5) (6). The review has expanded considerably and continues to incorporate evidence from several research approaches, with each approach constituting a section heading. As in previous compendia, the present synthesis includes sections dealing with single human gene mutations, genetically unidentified Mendelian disorders, quantitative trait loci (QTLs) from rodent and other animal model studies, association studies in humans with specific genes and mutations, human linkage studies including genome scans whose goals are to identify QTLs of obesity or obesity-related phenotypes, and a refined pictogram of the 2000 human obesity gene map. The references to each entry in the current human obesity gene map are provided for convenience.

The review includes publications that have dealt with a variety of phenotypes pertaining to obesity, including body mass index (BMI), body fat mass, percentage of body fat, fat-free mass, skinfolds, resting metabolic rates, plasma leptin levels, and other components of energy balance. As in previous updates, negative findings are not systematically reviewed but are briefly introduced when such data were available to us.

In this year's review, we are using gene symbols and chromosomal locations given in the Locus Link website (http:www.ncbi.nlm.nih.govLocusLink) available from the National Center for Biotechnology Information, which provides the official nomenclature of genetic loci.

We renew our request for feedback and comments on the part of the investigators who are interested in any aspects of the gene map and who would like to contribute to future editions of this publication. The electronic version of this publication will be available at the following address: http:www.obesity.chair.ulaval.cagenes.html. An expanded and more extensively cross-referenced version of the map can be accessed at

Single-Gene Mutations

We have added to single-gene mutation rodent models (Table 1) the attractin (Atrn) gene from the Mahogany mutation that suppresses diet-induced obesity. In humans, ATRN is located at 20p13 and encodes a transmembrane form of attractin (7).

Table 1.  Single-gene mutation rodent models of obesity*
MutationsChromosomeGenesInheritanceChromosomeGenesGene productReferences
  • *

    Status as of October 2000.

  • The strain carrying the adult (ad) dominant mutation on chromosome 7 is now extinct.

  • Homologous to rat fat (fa)/corpulent (cp).

Diabetes (db)4LeprRecessive1p31LEPRLeptin receptor140,141
Fat (fat)8CpeRecessive4q32CPECarboxypeptidase E142
Obese (ob)6LepRecessive7q31.3LEPLeptin143
Tubby (tub)7TubRecessive11p15.5TUBInsulin signaling protein144–146
Mahogany (mg)2AtrnRecessive20p13ATRNAttractin7,147
Agouti yellow (Ay)2AyDominant20q11.2–q12 Agouti signaling protein148

This last year has seen the discovery of another probable gene mutation explaining a human obesity syndrome (Table 2). Holder et al. (8) described a severely obese girl with a weight of 47.5 kg at 67 months of age (+9.3 SD) and a height of 1.27 m (+3.2 SD); no other anomalies were reported. She carried a de novo balanced translocation between chromosomes 1 and 6 (karyotype 46,XX,t(1;6)(p22.1;q16.2)), which disrupted the SIM1 gene, a critical transcription factor for the formation of supraoptic and paraventricular hypothalamic nuclei in mice. The latter nuclei are well known to be involved in energy homeostasis. The patient was heterozygous for a silent C → T substitution at nucleotide (nt) 1328 in exon 9, presumably associated with a loss of function of SIM1. Her energy expenditure was normal for her age and weight, implying that the mutation probably affected energy intake.

Table 2.  Cases of human obesity caused by single-gene mutations
GeneLocationMutationN*Age (range) yearsBMI (range) kg/m2References
  • N/A, not available.

  • *

    N, number of published cases.

LEPR1p31G→A (exon 16)313–1952.5–71.5149
POMC2p23.3G7013T and C7133Δ (exon 3) C3804A (exon 2)23–7N/A150
PCSK15q15-q21Gly483Arg A→C+4 (intron 5)13N/A151
SIM16q16.3-q21C→T nt 1328 (exon 9)16.629.58
LEP7q31.3G398Δ (codon 133)22–836.6–45.8152,153
  C→T (codon 105) (exon 3)46–3432.5–55.8154,155
MC4R18q22ΔCTCT nt 631–634 (codon 211)104–8127.7–419,10,156
  GATT insertion at nt 732 (codon 246)511–5830–57157
  C1O5A Tyr35X118–6425.9–56.69,10
  47-48insG A31G C52T C449T A508G C493T T749A T902C828–5241.5–64.511

Among the previously reported monogenic obesity syndromes, the only new published cases have been on carriers of mutations in the melanocortin-4 receptor (MC4R) gene. The German group that reported on six individuals in 1999 (9) expanded their study to three families, identifying a total of 19 carriers of either a 4-base pair (bp) deletion at codon 211 or a nonsense mutation at codon 35 (10). However, obesity status differed between carriers, suggesting variable penetrance. In a population of 209 severely obese (BMI of >40 kg/m2) French subjects, Vaisse et al. (11) reported on 8 carriers of eight different mutations in the MC4R gene not found in 366 normal weight controls. Several of the mutations appeared to have a functional impact. Thus far, of a total of 47 cases of monogenic forms of obesity involving 19 mutations in six different genes, MC4R mutations seem to be the most frequent, with a total of 11 mutations responsible for 34 cases.

Mendelian Disorders

Progress is ongoing in identifying genes or narrowing down the loci associated with the various adiposity-related Mendelian disorders described in the Online Mendelian Inheritance in Man database; a total of 24 syndromes with known map locations are given in Table 3.

Table 3.  Obesity-related Mendelian disorders with known map location*
Mode of inheritanceOMIM No.SyndromeLocusCandidate geneReferences
  • *

    Adapted from OMIM (Online Mendelian Inheritance in Man) computerized database.

  • N/A, not available.

  • Status as of October 2000.

Autosomal dominant100800Achondroplasia (ACH)4p16.3FGFR3158–161
 103580Albright hereditary osteodystrophy (AHO)20q13.2-q13.3GNAS117,162–172
 103581Albright hereditary osteodystrophy 2 (AHO2)15qN/A173
 105830Angelman syndrome with obesity (AGS)15q11-q13N/A174
 147670Insulin resistance syndromes (IRS)19p13.3-p13.2INSR175–182
 122000Posterior polymorphous corneal dystrophy (PPCD)20q11N/A183
 151660Familial partial lipodystrophy Dunnigan (FPLD)1q21.2-q21.3LMNA16,184–186
 176270Prader–Willi syndrome (PWS)15q12SNRPN NDN18–21,187
 190160Thyroid hormone resistance syndrome (THRS)3p24.3THRB188
 181450Ulnar-mammary syndrome or Schinzel syndrome (UMS)12q24.1TBX3189
Autosomal recessive203800Alstrom syndrome (ALMS1)2p13-p12N/A190,191
 209901Bardet–Biedl syndrome 1 (BBS1)11q13N/A22,23,192
 209900Bardet–Biedl syndrome 2 (BBS2)16q21N/A192,193
 600151Bardet–Biedl syndrome 3 (BBS3)3p13-p12N/A24,194
 600374Bardet–Biedl syndrome 4 (BBS4)15q22.3-q23MYO9A192,195,196
 603650Bardet–Biedl syndrome 5 (BBS5)2q31N/A197,198
 605231Bardet–Biedl syndrome 6 (BBS6)20p12MKKS25,26
 269700Berardinelli–Seip congenital lipodystrophy (BSCL)9q34N/A199
 216550Cohen syndrome (COH1)8q22-q23N/A200
 212065Carbohydrate-deficient glycoprotein type 1a (CDGS1A)16p13.3-p.13.2PMM227,28,201
 227810Fanconi–Bickel syndrome (FBS)3q26.1-q26.2SLC2A229–31,202
 139191Isolated growth hormone deficiency (IGHD)7p15-p14GHRH-R12,13
 601538Combined pituitary hormone deficiency (CPHD)5qPROP114,15
X-linked301900Borjeson–Forssman–Lehmann syndrome (BFLS)Xq26FGF13203,204
 303110Chroroideremia with deafness (CHOD)Xq21.1-q21.2N/A205,206
 300148Mehmo syndrome (MEHMO)Xp22.13-p21.1N/A207,208
 300218Mental retardation X-linked, syndromic 7 (MRXS7)Xp11.3-q22N/A33
 300238Shashi X-linked mental retardation syndrome (SMRXS)Xq26-q27N/A32
 312870Simpson–Golabi–Behmel 1 (SGBS1)Xq26.1GPC3, GPC434,209–215
  Simpson–Golabi–Behmel 2 (SGBS2)Xp22N/A216
 309585Wilson–Turner syndrome (WTS)Xp21.2-q22N/A217

In this year's update, because of the importance of growth hormone on body fat distribution, in particular its association with central adiposity, we have reviewed the hereditary growth hormone and pituitary hormone deficiency syndromes, for which several causal genes have been well-characterized in the last decade. We have only retained those syndromes for which overall or central obesity is clearly specified in the reports.

In the autosomal recessive category, isolated growth hormone deficiencies with mutations in the growth hormone-releasing hormone receptor gene have been described. Wajnrajch et al. (12) reported on two children with predominantly truncal obesity carrying a G → T transversion at nt 265, resulting in a Glu72Stop mutation and a truncated receptor. Salvatori et al. (13) described a G → A transition of nt 1 of the 5′ splice site at the beginning of IVS1 in 30 affected subjects of Brazilian origin with increased abdominal fat accumulation and severe growth retardation.

In the combined pituitary hormone deficiency syndromes, multiple endocrine axes can be affected with variable clinical expression. In particular, hereditary growth hormone deficiency syndrome and central hypothyroidism can lead to truncal obesity. The “Prophet of Pit-1” or PROP1 gene, controlling the ontogenesis of pituitary neuroendocrine cells, is involved in several reported cases of combined pituitary hormone deficiency syndromes. In 1999, Rosenbloom et al. (14) reported on eight subjects with a 2-bp 296delGA deletion, three of whom were over the 90th percentile for BMI with respect to height. Mendonca et al. (15) described two subjects carrying a 2-bp 301delAG deletion, both of whom had marked decreases in height but increases in weight relative to height.

Among the previously reported syndromes, in the autosomal dominant category, the major advance in the last year was the discovery of a gene explaining Dunnigan-type familial partial lipodystrophy, a syndrome in which peripheral subcutaneous fat is absent. Cao and Hegele (16) described five Canadian patients each carrying a novel G → A change at codon 482 in exon 8 (missense mutation R482Q) in the lamin A/C gene (LMNA), which undergoes alternative splicing to produce the nuclear lamin proteins lamin A and lamin C. No unaffected members of the five families carried the mutation.

Regarding other syndromes, several new mutations in the GNAS1 gene were reported by Aldred and Trembath (17), as well as a review of published mutations in patients with Albright hereditary osteodystrophy, a disorder in which obesity is one of the defining features. Prader–Willi syndrome (PWS) remains a subject of intense research, with a French group demonstrating the possible involvement of a novel imprinted gene in the PWS locus, the NDN gene, which is the human homologue of the mouse brain-specific nectin protein gene (18). Another group (19) reported a family with PWS in which affected members carried only submicroscopic deletions in the SNRPN gene and not in nearby loci, therefore confirming previous reports (20) (21) that the PWS imprinting center is located close to that gene.

In the autosomal recessive category, progress was made in Bardet–Biedl syndrome (BBS) patients. Katsanis et al. (22) narrowed down the type 1 (BBS1) locus, through linkage and haplotype analysis in 91 pedigrees of North American and European origin, to a 1.8-megabase region between markers D11S1883 and D11S4944 on chromosome 11. Young et al. (23) further reduced the BBS1 interval to a 1-cM region between markers D11S1883 and D11S4940, surrounding the phosphorylase glycogen muscle locus, in a study of families from Newfoundland, Canada. This same Canadian group also narrowed down the BBS type 3 locus through haplotype analysis to a critical 6-cM interval on chromosome 3 between D3S1595 and D3S1753 (24). Finally, a new BBS, type 6 (BBS6), mapping to 20p12, was described in the past year by two groups (25) (26). Both groups found the gene involved, known as the McKusick–Kaufman syndrome gene. It encodes for a chaperonin protein that plays a role in protein integrity. Affected individuals were either homozygotes or compound heterozygotes for several mutations in the McKusick–Kaufman syndrome gene.

In carbohydrate-deficient glycoprotein syndrome type 1a, a disorder caused by defective glycosylation of glycoconjugates resulting in severe encephalopathy with hypogonadism and lipodystrophy, several new mutations in the phosphomannomutase (PPM2) gene were reported (27) (28). Similarly, in the past year, three different groups (29) (30) (31) described several novel mutations in the solute carrier family 2 gene (SLC2A2), also known as the GLUT2 gene, in patients with Fanconi–Bickel syndrome, in whom there is sparse subcutaneous fat as well as hepatorenal glycogen accumulation.

In the last category, X-linked Mendelian disorders, two new syndromes have been described. Shashi et al. (32) reported on a large American family in which seven males had mental retardation with characteristic dysmorphic features and obesity. Linkage analysis established linkage to Xq26–27. Ahmad et al. (33) described a Pakistani family in which 10 males showed mental retardation, obesity, hypogonadism, and tapering fingers. Maximum linkage was obtained with the marker DXS1106.

Finally, in Simpson–Golabi–Behmel syndrome type 1, in which affected individuals have elevated birth weight and height as well as prenatal and postnatal overgrowth with slight obesity, Veugelers et al. (34) reported on several point mutations and one exon deletion in the glypican-3 (GPC3) gene in seven patients, predicting loss-of-function of the GPC3 protein.

QTLs from Cross-Breeding Experiments

The number of animal QTLs linked to body weight or body fat has increased by 17 since the last review (Table 4). A total of 115 animal QTLs have now been uncovered. Their equivalent syntenic regions in humans, when they can be determined from available maps, are shown in Table 4. When none was provided by the authors, we have proposed acronyms for QTLs to facilitate their inclusion in the map. Overall, the results of one mouse novel cross, two rat novel crosses, and one pig novel cross have been published. Some existing rat and pig crosses have also been further investigated.

Table 4.  QTLs reported for animal polygenic models of obesity with their putative syntenic locations in the human genome*
Crosses QTLStatisticsPhenotypesAnimalHumanReferences
  • r, replicated; Mob, multigenic obesity; Dob, dietary obese; Afw, abdominal fat weight; Afp, abdominal fat percent; Bl, body length; Bw, body weight; Obq, obesity QTL; Pfat, polygenic fatness; Qlw, QTL late weight gain (6–10 weeks); Qbw, QTL body weight; Qlep, QTL for leptin; Bw6, body weight at 6 weeks; Qfa, QTL LEPRfa; Nidd/gk, type 2 diabetes/Goto–Kakizaki; bw/gk, body weight/Goto–Kakizaki; Niddm, type 2 DM; Hlq, heat loss QTL; Fatq, fat QTL; Batq, brown adipose tissue QTL; Pfatp, predicted fat percentage; Dmo, diabetic mouse; Fob, fat obesity; Wokw, Wistar Ottawa Karlsburg Rt1

  • u

    W; SHR, salt hypertensive rat; SSC, swine chromosome; AFIFA, avian feed in take at a fixed age interval. p, paternal effect; m, maternal effect; N/A, not available.

  • *

    Synteny relationships established according to the following references: 84–88.

  • Also observed in the cross CAST/Ei × C57BL/6J (179).

  • Also observed in the CAST/Ei × C57BL/6J F2 intercross (193).

  • §

    Also observed in the cross (C3H/He × A/J) × Mus spretus (65).

  • Status as of October 2000.

MouseMus spretus×Mob1lod = 4.26.5% Percent fat716p12.1-p11.2218
 C57BL/6JMob2lod = 4.87.1% Femoral fat67q22-q31.3 
  Mob3lod = 4.87.0% Percent fat1214q31-q32 
  Mob4lod = 3.45.9% Mesenteric fat155p13 
MouseNZB/B1NJ× SM/JMob5lod = 3.636% Body fat220q12-q13219
MouseCAST/Ei× C57BL/6JMob6lod = 7.3Subcutaneous fat22q31-q37220
  Mob7lod = 5.7Subcutaneous fat22q23-q37 
  Mob8lod = 4.7Body fat (%)96q12-q13 
  Qleplod = 5.2Leptin level (no obesity)49p22 
  Bl/Bwlod = 4.3/2.5Body length/body weight158q22-q23 
MouseAKR/J× SWR/JDob1lod = 4.5N/A41p36.13-p35 9p13221
  Dob2lod = 4.87% Adiposity93p21222
  Dob3lod = 3.94% Adiposity158q23-q24 
MouseA/J× M. spretus ×Bw1§lod = 3.424% Body weightXXp11-q26223
 C57BL/6JBw2§lod = 6.6(3 QTLs together)XXq11-q13 
  Bw3lod = 4.3 XXp22-q27 
MouseJU/CBA× CFLP (P6 line)QbwXlod = 24.417 to 20% 10-week weightXXq26.3-q27.2224
MouseDu6× DuKQbw1lod = 2.76.9% Abdominal fat31p22-p21225
  Qbw2lod = 7.617% Body mass1117q12-q22 
MouseDu6× DukBw4F = 4.7923.1% Body weight1117p13-q23226
  Afw1/Afp1F = 4.8910 to 13% Abdominal fat41p36-q33 
  Afw2F = 4.798.3% Abdominal fat112p23-p12 
  Afw3F = 4.707.7% Abdominal fat131q41-q43 
  Afp2F = 4.898.3% Abdominal fat (%)31p36-q31 
Mouse129/Sv× Le/SuzObq1lod = 8.012.3% Adiposity719q13.2-q13.3227
  Obq2lod = 5.56.3% Adiposity 1q21-q23 
MouseAKR/J× C57L/JObq3lod = 5.17.0% Adiposity22q23-q31228
  Obq4lod = 4.66.1% Adiposity176q25-q27 
MouseKK/H1Lt × C57BL/6JObq5lod = 6.317% Adiposity (females)911q22-q24229
  Obq6lod = 5.011.7% Adiposity (males)XXq26-q28 
  KK7lod = 6.9/4.4Body weight/inguinal fat711q21 
MouseKK-A(y)× C57BL/6JBwq1lod = 3.115% Body weight4N/A230
  Bwq2lod = 3.4/4.119% Body weight/26% adiposity63p25 
MouseTSOD × BALB/cANidd5lod = 5.9110.9% Body weight22q23-q37231
  Nidd6lod = 4.659.2% Body weight11q25-q41 
MouseM16i× CAST/EiPfat1N/AAdiposity22p13-q21232
MouseMH× C57BL/6JHlq1lod = 5.64.7% Heat loss11q21-q41233
  Hlq2lod = 3.73.1% Heat loss211p14-p11 
  Hlq3/4lod = 3.8/4.73.1/3.9% Heat loss31p21-p13 
  Hlq5lod = 4.063.4% Heat loss74q28-q31 
  Fatq1lod = 8.05.9% Gonadal fat116p13-p11 
  Batq1lod = 4.03.3% Brown fat118q21.3-q22.1 
  Batq2lod = 3.52.8% Brown fat31q41-q42.1 
MouseDBA/2J× C57BL/6JBw6alod = 3.33% 6-week weight11q31-q33234
  Bw6blod = 3.34% 6-week weight49p24-p23 
  Bw6clod = 3.24% 6-week weight54q12-q13 
  Bw6dlod = 4.35% 6-week weight512q24 
  Bw6elod = 4.04% 6-week weight62p12 
  Bw6flod = 6.99% 6-week weight715q11-q13 
  Bw6glod = 4.45% 6-week weight96q12-q16 
  Bw6hlod = 5.76% 6-week weight1117p13 
  Bw6ilod = 4.14% 6-week weight1315q23-q25 
  Bw6jlod = 3.03% 6-week weight143p21 
  Bw6klod = 4.97% 6-week weight176p21 
MouseDBA/2J× C57BL/6JPfatp4lod = 5.020% Predicted fat49p24235
  Pfatp6lod = 4.9(4 QTLs together)63p14.1-p12 
  Pfatp13lod = 5.3 135q22-q31 
  Pfatp15lod = 8.6 158q24-qter 
MouseQuackenbush-Swiss× C57BL/6JQsbwp < 0.00940% Body weight1012q22-q23236
MouseLG/J × SM/JQlw1lod = 2.31.9% Late weight gain12q11-q1236,37
  Qlw2lod = 2.92.6% Late weight gain220p11 
  Qlw3lod = 2.38.4% Late weight gain33q25-q26 
  Qlw4lod = 2.4r2.4% Late weight gain46q16 
  Qlw5lod = 2.8r3.4% Late weight gain63p26-p24 
  Qlw7lod = 2.0r2.0% Late weight gain715q26 
  Qlw9lod = 2.5r2.4% Late weight gain911q21 
  Qlw10lod = 2.3r1.9% Late weight gain1017q22-q24 
  Qlw11lod = 2.62.4% Late weight gain1122q12 
  Qlw12lod = 2.32.4% Late weight gain122p24-p23 
  Qlw13lod = 2.44.4% Late weight gain131pter-q42 
  Qlw14lod = 3.12.9% Late weight gain148p23 
  Qlw18lod = 1.63.0% Late weight gain185q31-q33 
MouseNSY× C3H/HeNidd3nsylod = 6.8Epididimal fat612p237
MouseF× LFob1lod > 3.34.9% 14-weeks % fat22q22-qter 35
  Fob2lod > 3.319.5% 14-weeks % fat127p22-q22 
    (female) 14q12-q13 
  Fob3lod = 11.314.4% 14-weeks % fat158q22-q24 
  Fob4lod > 3.37.3% 14-weeks % fatXXp22-p21 
RatLeprfa/Leprfa 13M× WKYQfa1lod = 2.35.4% Weight (male)116q13238
   lod = 2.55.8% BMI (male) 16p11 
   lod = 2.26.9% BMI (female) 11p15 
  Qfa12lod = 2.77.8% Weight (female)127q22 
   lod = 3.08.3% BMI (female)   
RatGK× BNNidd/gk1N/A13% Adiposity13p21239
  Nidd/gk5N/A9% Body weight811q22-q23 
  Nidd/gk6N/A7% Body weight171q41-q44 
  bw/gk1N/A24% Body weight78q21-q24 
RatGK× FNiddm1lod = 3.223.5% Body weight110q24-q26240
  Niddm3lod = 3.0N/A1017pter-q23 
  Weight1lod = 6.2N/A712q22-q23 
RatOLETF× BNDmo1lod = 6.011.6% Body weight110q23-q24 40
Rat(OLETF× BN)× OLETFDmo1lod = 8.2–14.0Adipose index, fat weight, body weight110q23-q24 41
  Dmo4lod = 4.4–5.5Fat weight, adipose index111p15.5-p15.4 
  Dmo5lod = 3.5–3.6Fat weight, adipose index319p13.2-q13.3 
  Dmo6plod = 3.5–3.6Fat weight, adipose index614q32 
  Dmo7plod = 4.9–5.4Fat weight, adipose index712q22-q23 
  Dmo9lod = 3.5Adipose index113q26.1-q28 
  Dmo10lod = 3.5–3.6Fat weight, body1121q22.1 
    weight 22q11.2 
RatDahl× MNSDAHL3p < 0.0000313% Body weight310q25241
RatSHR × BB/OKSHR1lod = 3.332% Body weight (males)111p15.5242
  SHR4lod = 3.114% Body weight (females)47p15.3 
RatWOKW× DA/KWokw1lod = 4.931% 30-week body13p21 38
    weight 10q24-q26 
  Wokw2lod = 4.516% BMI51p36-p31 
PigEuropean wild boar× Large whiteFAT1N/AN/A41q21-q25243
   F = 15.8/18.6Back/abdominal fat  244
   p < 0.000115.4% Visceral fat  245
   p < 0.00017.3% Subcutaneous fat   
   p < 0.00019.7% Body fat (%)   
PigWild Boar× Large whiteIGF2qF = 7.110.4% Back fat depth2p11p15.5246,247
PigMeishan× Large whiteBFM4N/AMidback fat depth41q21-q25248
PigMeishan× Duroc, Hampshire, LandracePig QTL2p < 0.01, F = 7.9Average back fat76p2144,249
 Minghu× Hampshire, LandracePIT1F = 3.3442-day weight133p1145
PigMeishan × (DutchSSC2F = 2.7rBack fat thickness211p15250
 Landrace× LargeSSC7F = 18.0rBack fat thickness76p21.3251
 white)    15q22-qter 
PigMeishan × DutchSSC2F = 24.1Back fat thickness (p)211p15 43
  SSC6pF = 14.5Intramuscular fat (m)6p16q22-qter 
  SSC6qF = 14.7Intramuscular fat (p)6q1p33-p32 
  SSC7F = 30.3/49.4Back fat thickness (p/m)76p22-p21.3 
PigMeishan× DutchSSCXF = 22.61.0 to 1.5% Back fat thicknessXXq11.2-q22 42
   F = 12.80.1 to 0.2% Intramuscular fat   
PigMeishan× White compositeSSC1F = 15.4Back fat thickness19q32-q34.1252
  SSC7F = 14.7Back fat thickness76p21.3 
  SSCXF = 32.3Back fat thicknessXX 
ChickenWhite Plymouth Rock× White Plymouth RockAFIFA12.8Food intake1N/A253

A new mouse cross between outbred lines divergently selected for 53 generations for high-fat (fat or F line) or low-fat (lean or L line), and presenting a 5-fold difference in percentage of fat at 14 weeks of age, allowed the detection of four QTLs (Fob1 to Fob4) related to percentage of fat on chromosomes 2, 12, 15, and X (35). Five of the QTLs previously reported for late body weight gain (36) were replicated on chromosomes 4, 5, 7, 9, and 10 in a second F2 intercross of the LG/J and SM/J mouse strains (37). The Wistar Ottawa Karlsburg with RT1u haplotype (W) of the major histocompatibility complex (WOKW) rat strain, which develops the main features of syndrome X such as moderate hypertension, dyslipidemia, hyperinsulinemia, obesity, and impaired glucose tolerance (38), has been crossed to the Dark Agouti/Karlsburg strain. Two new QTLs (WOKW1 and WOKW2) related to body weight and BMI and located, respectively, on chromosome 1 and chromosome 5 (39) have been reported. A QTL for body weight (Dmo1) previously identified from a cross between the diabetic OLETF × BN rat strains (40) was replicated in a backcross to the OLETF strain (41). In addition, new QTLs related to fat weight, body weight, or adipose index on chromosomes 1 (Dmo4), 3 (Dmo5), 6 (Dmo6p), 7 (Dmo7p), and 11 (Dmo9 and Dmo10) were identified.

In a pig cross involving the obese Chinese Meishan breed and lean Dutch White production lines, one QTL (SSCX) for back fat thickness and intramuscular fat content has been detected on chromosome X, near the phosphoglycerate kinase 1 gene (42). In the same cross, paternally or maternally expressed QTLs were also observed for back fat thickness on chromosomes 2 (SSC2) and 7 (SSC7), and two other QTLs (SSC6p, SSC6q) were observed for intramuscular fat on chromosome 6 (43). Finally, in a mix of five different crosses (Meishan × Duroc or Hampshire or Landrace; Minzhu × Hampshire or Landrace) analyzed previously (44), a QTL for back fat thickness at the pituitary specific transcription factor 1 gene, encoding an essential transcriptional regulatory factor of growth hormone, prolactin, and thyrotropin β subunit, was identified on chromosome 13 (45).

We have defined, when not provided by the authors, the putative syntenic relationships with human chromosomes for the QTLs identified in Table 4. To establish the synteny, the position of the markers defining the QTL, according to the Mouse Genome Database from The Jackson Laboratory (Bar Harbor, ME) (46), was compared with the equivalent region in the human genome using the integrated linkage maps of the Mouse/Human homology maps (47). For the rat, the maps described by Yamada et al. (48) and Jacob et al. (49) were used. For the pig and the chicken, maps from the Animal Genome Database in Japan (50) and from the U.S. Livestock Genome Mapping Projects (51) were used.

Association Studies

The evidence for associations between candidate genes and obesity-related phenotypes is summarized in Table 5. Altogether 130 studies have reported significant associations involving a total of 48 candidate genes. Studies published over the past year have shown significant associations of BMI, body weight, and obesity with polymorphisms in TNFRS1B (52), LEPR (53) (54), LMNA (55), peroxisome proliferator activated receptor, gamma (PPARG) (56) (57) (58), UCP1 (59), UCP2 (60) (61) (62), UCP3 (63), NPY5R (64), GRL (65), ADRB2 (66) (67) (68), ADRB3 (69) (70), tumor necrosis factor, alpha (TNFA) (71) (72), NPY (73), LEP (74), INS (75), APOA4 (76), DRD2 (77), GNB3 (78), MC4R (11), LDLR (79), and HTR2C (80). Fat mass and/or percentage of body fat was associated with markers of LEPR (53), CCKAR (81), TNFA (72), UCP2 (60) (61), and APOA4 (76). Polymorphisms in the NPY (82) and GNB3 (83) genes have been reported to be associated with birth weight. Abdominal obesity phenotypes (abdominal visceral and subcutaneous fat, waist girth, waist-to-hip ratio, and abdominal sagittal diameter) showed associations with LEPR (54), LMNA (55), PPARG (56) (57), CART (84), GRL (65), ADRB2 (67), NPY (73), ADRB3 (66), and ADRA2A (66) markers. Polymorphisms in the UCP2 (60), DRD2 (85), and LDLR (79) loci have been reported to be associated with skinfold thickness phenotypes. Plasma leptin levels have been found to be associated with DNA sequence variation in the TNFRS1B (52), LMNA (86), PPARG (57), CCKAR (81), GRL (65), and ADRB2 (87) markers. Finally, a HTR2A gene polymorphism was associated with dietary energy and carbohydrate and alcohol intake in obese subjects (88), and the LMNA gene was associated with familial partial lipodystrophy (89).

Table 5.  Evidence for the presence of an association between markers of candidate genes with BMI, body fat, and other obesity-related phenotypes
GeneLocationN (cases)Phenotypep valueReferences
  1. Status as of October 2000.

  2. FFM, fat-free mass; WHR, waist-to-hip ratio; RQ, respiratory quotient; TER, trunk-to-extremity skinfolds ratio; BMR, basal metabolic rate; DM, diabetes mellitus; LBM, lean body mass; CAD, coronary artery disease; BW, body weight; NPRQ, non-protein respiratory quotient; FATOX/LBM, fat oxidation adjusted for lean body mass; EE, energy expenditure; SPA, spontaneous physical activity; FM, fat mass.

TNFRSF1B1p36.3-p36.2217BMI, leptin<0.0552
LEPR1p3120% Fat0.003254
  308FFM in subjects with BMI ≥ 270.03 to 0.05255
  130Extreme obesity in children0.02 to 0.04256
  502BMI, FM0.005 to 0.0353
  267BMI, abdominal sagittal diameter0.041 and 0.04654
HSD3B11p13.113212-year changes in Σ6 skinfolds0.04257
LMNA1q21.2-q21.348Leptin, leptin to BMI ratio in partial lipodystrophy families<0.0586
  306BMI, WHR, leptin in Canadian Oji-Cree<0.0555
  47Familial partial lipodystrophy<0.000189
ATP1A21q21-q23122% Fat, RQ<0.05258
  156RQ in young adults0.0001259
  94FM in women ≥ 42 years0.008 to 0.02261
ACP12p2575BMI in children0.02262
  265BMI in type 2 DM subjects0.002263
  56% Fat, abdominal fat0.04266
POMC2p23.3337Leptin in Mexican Americans0.001267
ADRA2B2p13-q13166BMR in obese nondiabetics0.01268
IRS12q361748Current BMI and ΔBMI since age 25 in African Americans0.04 to 0.05269
  156Leptin in obese subjects0.03270
PPARG3p25820Leptin in obese subjects0.001271
  333BMI in middle-aged subjects0.03272
  973BMI in elderly subjects0.02 
  752ΔBMI in obese men0.002 to 0.008273
  869ΔBMI in lean men  
  141BW, BMI, LBM, fat mass, waist and hip girths0.002 to 0.05275
  375Severe obesity with early onset<0.0558
  921BMI, waist girth, leptin in Mexican Americans0.015 to 0.02857
  838BW, height, BMI, waist girth0.002 to 0.0456
CCKAR4p15.2-p15.11296% Fat, leptin0.003 to 0.04181
FABP24q28-q31395Abdominal fat0.008277
  507BMI, % fat0.01278
UCP14q28-q31123High fat gainers over 12 years0.05279
  163Weight and BMI loss<0.05280
  113Weight loss in Japanese women0.001281
  526BMI in overweight women0.0259
NPY5R4q31-q3274Obesity (BMI 40–47 kg/m2) in Pima Indians<0.0564
CART5q612WHR in men0.002184
GRL5q31-q3251Abdominal visceral fat in lean subjects0.003 < p < 0.007282
  262BMI, WHR, abdominal sagittal diameter, leptin0.001 to 0.03965
ADRB25q31-q32140BMI, fat mass, fat cell volume0.001 < p < 0.009283
  508BMI in Japanese subjects0.001284
  836Body weight, BMI, waist circumference, hip circumference, WHR in sedentary French men<0.002285
  574BMI in Japanese subjects0.009 to 0.003286
  277BMI in Japanese men0.004287
  826Obesity, BMI, waist circumference, hip circumference, WHR0.05 to 0.0167
  224BMI > 35 kg/m2 in men0.0166
  180BMI0.003 to 0.0268
TNFA6p21.338% Fat0.02288
  110Obesity (27 < BMI < 35 kg/m2)0.0271
  378BMI, % fat in women0.0272
GCK7p15.3-p15.158Birth weight in boys only0.002292
NPY7p15.1369Birth weight0.0382
  595BMI, WHR0.03 to 0.0473
PON27q21.3100Birth weight in Trinidadian neonates of South Asian origin<0.05293
LEP D7S2519,7q31.3168Weight loss0.006 < p < 0.007294
649, 530, 1875 84Body weight0.05295
   Leptin response to diet0.005 
  103BMI, body weight<0.05298
  211Severe obesity in women0.017 to 0.03574
LPL8p22236BMI (leanness)0.05299
ADRB38p12-p11.2128Weight gain over 25 years0.01300
  185Weight gain over 20 years, current weight0.007 < p < 0.03301
  335WHR in women0.02302
  254Early onset obesity0.002306
  131Abdominal visceral fat, fat mass<0.01307
  398Visceral/subcutaneous abdominal fat, BMI0.02 < p < 0.03308
  83BMI in CAD patients<0.05309
  586BMI and hip circumference in women<0.03311
  56BMI, fat mass, waist circumference<0.05312
  211Moderate obesity0.02314
  179ΔBMI during pregnancy0.006 to 0.02315
  76FM in Thai males<0.05316
  553Obesity in Japanese children0.0270
  213Total and subcutaneous abdominal fat0.018 and 0.02966
CBFA2T18q22281% fat, BMI, waist and hip circumference0.0002 < p < 0.02317
ADRA2A10q24-q2672TER in women0.002318
  476Total and subcutaneous abdominal fat0.012 and 0.00366
SUR111p15.1232Morbid obesity0.02319
INS11p15.5758Birth weight0.009321
  52WHR in obese women0.005322
UCP211q1382Sleeping and 24-hour metabolic rate0.007 < p < 0.04323
  790BMI in subjects >45 years0.04 
  220BMI in South Indian women0.02324
  143BMI in South Indian parents of type 2 DM probands<0.001 
  6024-hour EE, 24-hour SPA, sleeping SPA, 24-hour nonprotein RQ, 24-hour fat oxidation0.005 to 0.05325
  105BW, BMI, % overweight, % fat, FM, 4 skinfolds and their sum0.001 to 0.0560
  813Obesity (BMI > 30 kg/m2)0.00262
  41BW and FM gain in peritoneal dialysis patients<0.0561
UCP311q13120BMI, RQ, NPRQ, FATOX/LBM in African Americans0.008 to 0.04326
  382Current BMI, maximal BMI and BW during diet therapy in morbidly obese patients0.02 to 0.04327
  401BMI in morbidly obese subjects0.003763
APOA411q23375BMI and WHR in young men without family history of MI0.004328
  613BMI, % fat0.004 to 0.02376
DRD211q22.2-q22.3392Relative weight0.002329
  383Iliac and triceps skinfold0.002 to 0.03985
  176Obesity (BMI > 30 kg/m2)0.002 to 0.00377
GNB312p13197BMI in hypertensives0.02330
  1950Body weight and BMI in young white, Chinese, and black African males0.001 to 0.05331
  213BMI, waist and hip girths and skinfolds in Nunavut Inuit<0.05332
  230BMI in primiparous women0.0178
  181Babies’ birth weight (mothers’ genotype)0.01583
IGF112q22-q23502FM, % Fat, FFM,<0.05333
   ΔFFM after 20-week endurance training0.005 
CD36L112q24.1-q24.3288BMI in healthy lean women0.004 to 0.03334
HTR2A13q14-q21276Dietary energy and carbohydrate and alcohol intake in obese subjects0.028 to 0.04788
MC5R18p11.2156BMI in females0.003335
MC4R18q22156FM, % fat, FFM in females0.002 < p < 0.004335
INSR19p13.3-p.13.275Obesity (BMI > 26) in hypertensives0.05336
LDLR19p13.384BMI in hypertensives0.004337
  112BMI in hypertensives0.04338
  83BMI in normotensives0.008339
  270Obesity (BMI ≥ 26)0.02340
  131BMI, triceps and subscapular skinfold, arm fat index0.001 to 0.02179
ADA20q12-q13.11273BMI in type 2 DM subjects0.0004 to 0.01343
HTR2CXq24589BMI > 28 kg/m20.009 to 0.0280

Gene–gene and gene–environment interactions on obesity-related phenotypes have also been reported. In the Québec Family Study cohort, significant interactions were reported between the ADRA2A and ADRB3 polymorphisms on abdominal total and subcutaneous fat (66). In a group of obese German women, those who carried a rare allele in both the ADRB3 and IRS1 loci (n = 6) lost less weight during a weight loss program than those who were homozygotes for the common allele at both loci (90). In a cohort of Finnish type 2 diabetics and nondiabetic controls, subjects who carried a rare allele at both the ADRB3 and UCP1 loci (n = 11) gained more weight during a 10-year follow-up period than those who were homozygotes for the wild-type allele (91). In a cohort of morbidly obese patients, Otabe et al. (63) reported a significant inverse association between physical activity level and BMI in the homozygotes for the common allele in the UCP3 locus, whereas no association was found in other genotypes. An association between a GNB3 polymorphism and BMI that was detected in primiparous sedentary women was not observed in their physically active counterparts (78).

In addition to the 40 new studies with positive findings, we found 58 studies showing no associations between obesity-related phenotypes and selected candidate genes. Among the negative studies, the most frequent ones were those performed with markers of ADRB3 (six studies) (62) (92) (93) (94) (95) (96), PPARG (seven studies) (97) (98) (99) (100) (101) (102) (103), LPL (four studies) (94) (104) (105) (106), and UCP1 (four studies) (62) (91) (94) (96). Other markers yielding negative findings were related to ADRB2 (107) (108), LEP (109) (110), LEPR (70) (110), LIPC (111), CART (112) (113), TCF1 (114) (115), TNFA (116) (117) (118), UCP2 (119), UCP3 (120), APOA4 (121), DRD2 (64), DRD4 (122), VDR (123) (124), ESR1 (123), BRS3 (125), MC3R (126), MC4R (127), APOE (128) (129), HNF4A (114), IRS1 (90) (114) (130), HNF6 (114), IGF1R (131), IGF1 (131), INSR (132), and adiponectin (133). It should be noted that the majority of the studies with positive findings also reported nonsignificant associations with other obesity-related phenotypes and/or candidate gene markers. Thus, the actual number of negative findings is considerably higher than suggested by the above list.

Linkage Studies

A summary of the loci that have been shown to be linked to obesity-related phenotypes in genome-wide scans or other linkage studies is presented in Table 6. A total of 59 genes or loci have provided significant evidence of linkage with obesity-related phenotypes. Three genome-wide scans for obesity-related phenotypes were reported since last year's review. One of these genome-wide scans was performed in 193 Finnish obese (BMI of ≥30 kg/m2) sibpairs using 374 markers with an average density of 10 cM (134). The strongest evidence of linkage to obesity was obtained on chromosome Xq24 with DX6804, which had a maximum likelihood score of 3.14. Another obesity QTL was detected on chromosome 18q21, where a maximum likelihood score of 2.42 was obtained between obesity and D18S1155 (134). The results of a genome-wide scan for fat-free mass assessed from underwater weighing measurements were also reported in the Quebec Family Study (135). In the latter study, based on 292 markers with an average intermarker distance of 11.9 cM and typed on a maximum of 336 sibpairs, significant evidence of linkage with fat-free mass was found with three markers (IGF1R, D15S652, and D15S657) on chromosome 15q25-q26. Two other chromosomal regions also provided evidence of linkage with fat-free mass (FFM): one on 18q12 with D18S877 (logarithm of odds [lod] = 3.5) and D18S535 (lod = 3.6) and another on 7p15.3 with D7S1808 (lod = 2.7). Another genome scan for loci linked to plasma leptin concentrations was reported in Pima Indians (113) based on a total of 1199 sibpairs. The strongest evidence of linkage with age- and gender-adjusted plasma leptin concentrations was found on chromosome 6p21 (lod = 2.1) near the marker D6S271 at a map distance of 54 cM from the p-terminal (113). Using the Haseman–Elston sibpair linkage method, the best evidence of linkage with plasma leptin was found with the marker D16S265 on chromosome 16q21 near the BBS2 locus (113).

Table 6.  Evidence for the presence of linkage with obesity-related phenotypes
Gene*MarkersLocationN (pairs)Phenotypesp or lod valueReferences
  • RQ, respiratory quotient; RMR, resting metabolic rate; TER, trunk-to-extremity skinfolds ratio; WHR, waist-to-hip circumferences ratio; EE, energy expenditure.

  • *

    See Appendix for the complete name of the gene. The absence of a gene symbol indicates that the linkage study involved at argeted chromosomal region. QTL means human quantitative trait locus identified from a genome scan.

  • Status as of October 2000.

PGD 1p36.2-p36.13>168Suprailiac skinfoldp = 0.03344
 D1S193,200,4761p35-p31202–251BMI, Σ6 skinfolds, fat mass0.009 < p < 0.02345
LEPRQ223R, CA (IVS 3), CTTT (IVS 16)1p31268–324BMI, Σ6 skinfolds, fat mass, fat-free mass0.005 < p < 0.05255
QTLD1S5501p31-p2123624-hour RQlod = 2.8346
ATP1B1 1q22-q2594RQp = 0.04258
ATP1A2 1q21-q23289RQp = 0.02259
ACP1 2p25>300BMIp = 0.004347
   >168Triceps skinfoldp = 0.02344
QTLD2S17882p21>5000 Relative pairsLeptin, fat masslod = 4.9/2.8348
 D2S1788 720 Subjects; 230 familiesLeptin, BMI0.008 < p < 0.03349
 D2S1788 337 IndividualsLeptinlod = 7.5267
QTLD2S165,3672p22-p21264Leptinlod = 2.4/2.7136
IGKC 2p12>168Triceps skinfoldp = 0.03344
QTLD3S24323p24.2-p22377% Fatlod = 2.0350
GYPA 4q28.2-q31.1160TERp = 0.02351
QTLD5S4265p11264Leptinlod = 2.9136
ISL1 5q22.3226Obesityp = 0.03352
   284BMI, leptin0.0004 < p < 0.006 
GRL 5q31-q3288BMI >27p = 0.009353
ADRB2 5q31-q3266TERp = 0.02318
BF 6p21.3>168Triceps, subscapular, suprailiac skinfolds0.01 < p < 0.03344
TNFATNFir24, D6S273,2916p21.3>255% Fat0.002 < p < 0.05289
GLO1 6p21.3-p21.1>168Suprailiac skinfold, relative weight0.004 < p < 0.05344
QTLD6S2716p211199Leptinlod = 2.1113
NPY 7p15.1545Principal component of height, weight, skinfolds, abdominal and hip circumferencesp = 0.05354
   170Obesityp = 0.04 
QTLD7S18087p15.3336Fat-free masslod = 2.7135
LEP 7q31.347Body fatp = 0.008355
 D7S680,514,530 60BMI > 350.002 < p < 0.009356
 D7S504,1875 59BMI ≥ 40p = 0.04357
   88BMIp = 0.04358
 D7S504 46BMI > 85th percentilep = 0.001359
 D7S514,495 545BMI, skinfolds, fat, waist circumference0.0001 < p < 0.02360
 D7S1875 545WHRp = 0.009354
KEL 7q33402BMI, Σ6 skinfolds<0.0001351
ADRB3,D8S11218p12-p11.2470 Subjects from 10 large pedigreesBMIlod = 3.2361
QTLD8S11108q11.1>5000 Relative pairsLeptinlod = 2.2348
ORM1 9q31-q32>168Suprailiac skinfoldp = 0.03344
AK1 9q34.1>168Suprailiac skinfoldp = 0.01344
QTLD10S19710p12.3264Obesitylod = 4.9136
 D10S204,193,1781 and TCF810p11.22386 Subjects from 93 familiesObesity1.1 < lod < 2.5137
SUR1D11S41911p15.167BMI ≥ 27p = 0.003319
CCKBR 11p15.4221Leptinp = 0.01352
UCP2/UCP3 11q13240 Relative pairsRMRp = 0.000002362
QTLD11S2000,236611q22277% Fatlod = 2.8350
 D11S236611q22451% Fatlod = 2.1346
QTLD11S97611q2323624-hour EElod = 2.0346
QTLD11S91211q241766BMIlod = 3.6138
IGF1 12q22-q23352Visceral fatp = 0.02333
ESD 13q14.1-q14.2194Σ6 skinfolds, % fatp < 0.04351
QTLIGF1R, D15S652, 65715q25-q26336Fat-free mass2.0 < lod < 3.6135
QTLD16S26516q211199Leptinlod = 20.0113
MC5R 18p11.2242 to 289BMI, Σ6 skinfolds, fat mass, % fat, fat-free mass, RMR0.001 < p < 0.02335
MC4R 18q22210RQp = 0.04335
   105Obesity0.001 < p < 0.003363
QTLD18S877,53518q12336Fat-free masslod = 3.6135
QTLD18S87718q21451% Fatlod = 2.3346
QTLD18S11518q21193Obesitylod = 2.4134
ADA 20q12-q13.11428BMI, Σ6 skinfolds0.02 < p < 0.001351
 ADA, D20S17,12020q12-q13139 to 226BMI, Σ6 skinfolds, fat mass, % fat0.004 < p < 0.02219
 MC3R20q13.2-q13.3212 to 258BMI, Σ6 skinfolds, fat mass0.008 < p < 0.02219
QTLD20S60120q11.223624-hour RQlod = 3.0346
QTLD20S107,211,14920q13423BMI > 30, % fat3.0 < lod < 3.2364
P1 22q11.2-qter>168Relative weightp = 0.03344
QTLDXS6804Xq24193Obesitylod = 3.1134

In an attempt to replicate the linkage previously reported with obesity on chromosome 10p12 in French families (136), Hinney et al. (137) genotyped 11 markers spanning ∼23 cM from 10p13 to 10q11 in a sample of 386 individuals from 93 German families that had at least two obese children. The marker D10S197, which provided the strongest evidence of linkage in the French study (136), showed a lod score of 1.7 in the German families. In the German study (137), evidence of linkage to obesity was observed with markers D10S204 (lod = 2.0), D10S193 (lod = 1.1), TCF8 (lod = 2.4), and D10S1781 (lod = 2.2), which are ∼5 cM more centromeric than D10S197. These results suggest the presence of an obesity QTL on chromosome 10p11.2 near the centromere. To determine whether genetic variation in the DRD2 gene locus could be responsible for the linkage reported with BMI on 11q24 after a genomic scan in Pima Indians (138), a total of 1187 Pima Indians were genotyped for two polymorphisms within the DRD2 gene (64). The effect of the DRD2 polymorphisms on the 11q24 linkage signal was evaluated by repeating the chromosome 11 linkage analyses and comparing the lod scores obtained from a model that included the DRD2 genotypes with the lod scores obtained from a model that did not include these genotypes. The results of these linkage analyses were the same regardless of whether or not the DRD2 genotypes were included (64), suggesting that the DRD2 polymorphisms are not responsible for the linkage of BMI to chromosome 11q24 in Pima Indians. Finally, a linkage exclusion analysis of the chromosomal region 11q13 containing the UCP2 and UCP3 genes, performed in 458 individuals from 10 randomly ascertained Mexican American families, revealed that genetic variation around the UCP2 and UCP3 genes was unlikely to exert an influence on BMI, fat mass, waist circumference, and plasma leptin levels (139).


Figure 1 depicts the human obesity gene map and incorporates the loci from single-gene mutation rodent models of obesity, human obesity cases due to single-gene mutations, QTLs from crossbreeding experiments and genome-wide scans, all relevant Mendelian disorders that have been mapped to a chromosomal region, and genes or markers that have been shown to be associated or linked with an obesity phenotype. The map reveals that putative loci affecting obesity-related phenotypes are found on all but chromosome Y of the human chromosomes.

Figure 1.

Figure 1.

The 2000 human obesity gene map. The map includes all putative obesity-related phenotypes identified from the various lines of evidence reviewed in the article. The chromosomes and their regions are from the Gene Map of the Human Genome website hosted by the National Center for Biotechnology Information, National Institutes of Health (Bethesda, MD) ( The chromosome number and the size of each chromosome in megabases (Mb) are given at the top and bottom of the chromosomes, respectively. Loci abbreviations and full names are given in the Appendix. The abbreviations for animal QTLs are given in Table 4.

Figure 1.

Figure 1.

The 2000 human obesity gene map. The map includes all putative obesity-related phenotypes identified from the various lines of evidence reviewed in the article. The chromosomes and their regions are from the Gene Map of the Human Genome website hosted by the National Center for Biotechnology Information, National Institutes of Health (Bethesda, MD) ( The chromosome number and the size of each chromosome in megabases (Mb) are given at the top and bottom of the chromosomes, respectively. Loci abbreviations and full names are given in the Appendix. The abbreviations for animal QTLs are given in Table 4.

The number of genes and other markers associated or linked with human obesity phenotypes continues to expand. The progress made over the last decade is exemplified by the numbers collated in Table 7. It is obvious that the human obesity gene map has become significantly more detailed and complex since the first version developed in 1994. Of course, some of these loci will turn out to be more important than others, and many will eventually be proven to be false positive. The main task, including the identification or the positional cloning of the QTL genes, remains to identify the combination of genes and mutations that are contributing most to human obesity and to define under which environmental circumstances. It is also likely that the topic of gene–gene interactions will receive more attention in the coming years.

Table 7.  Evolution in the Status of the Human Obesity Gene Map
  • *

    Number of genes, not number of mutations.

  • From references 1 to 6 plus this review.

Single-gene mutations*2666
Mendelian disorders with map location8121316162024
Candidate genes with positive findings9101321294048
Animal QTLs7924556798115
Human QTLs from genome scans381421
Other human linkages991517293738


The research of the authors on the genetics of obesity is funded by the Medical Research Council of Canada (Grants MT-13960 and GR-15187). C.B. is supported by the George A. Bray Chair in Nutrition. We thank Diane Drolet for her dedicated contribution to the compendium and the development of the manuscript. The list of genes and markers currently in the map as well as the pictorial representation of the map is also available on the website of the Donald B. Brown Research Chair on Obesity at the following address: http:www.obesity.chair.ulaval.cagenes.html and on the website of the Pennington Biomedical Research Center Human Genomics Laboratory at: