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Keywords:

  • obesity;
  • linkages;
  • QTL;
  • genes;
  • Mendelian syndrome

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Single Gene Mutations
  5. Mendelian Disorders
  6. Quantitative Trait Loci (QTL) from Crossbreeding Experiments
  7. Association Studies
  8. Linkage Studies
  9. Conclusions
  10. Acknowledgments
  11. References

This report constitutes the sixth update of the human obesity gene map incorporating published results up to the end of October 1999. Evidence from the rodent and human obesity cases caused by single gene mutations, Mendelian disorders exhibiting obesity as a clinical feature, quantitative trait loci (QTL) uncovered in human genome-wide scans and in crossbreeding experiments with mouse, rat, pig and chicken models, association and linkage studies with candidate genes and other markers is reviewed. Twenty-five human cases of obesity can now be explained by variation in five genes. Twenty Mendelian disorders exhibiting obesity as one of their clinical manifestations have now been mapped. The number of different QTLs reported from animal models reaches now 98. Attempts to relate DNA sequence variation in specific genes to obesity phenotypes continue to grow, with 89 reports of positive associations pertaining to 40 candidate genes. Finally, 44 loci have linked to obesity indicators in genomic scans and other linkage study designs. The obesity gene map depicted in Figure 1 reveals that putative loci affecting obesity-related phenotypes can be found on all autosomes, with chromosomes 14 and 21 showing each one locus only. The number of genes, markers, and chromosomal regions that have been associated or linked with human obesity phenotypes continues to increase and is now well above 200.

imageimage

Figure 1. The 1999 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 web site hosted by the National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD (URL:http:www.ncbi.nlm.nih.gov). 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 QTLs are given in Table 4.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Single Gene Mutations
  5. Mendelian Disorders
  6. Quantitative Trait Loci (QTL) from Crossbreeding Experiments
  7. Association Studies
  8. Linkage Studies
  9. Conclusions
  10. Acknowledgments
  11. References

This 1999 update of the status of the human obesity gene map is the sixth in this series, which began as a chapter in the proceedings of the 7th International Congress on Obesity held in 1994 (1) followed by four subsequent yearly updates published in Obesity Research (2, 3, 4, 5). The present review provides an overview of the data reported from peer-reviewed papers as of the end of October 1999, on human obesity genes and markers. The review incorporates data accumulated from five lines of evidence: rodent and human obesity cases caused by single gene mutations; Mendelian disorders exhibiting obesity as a clinical feature; quantitative trait loci (QTL) uncovered in human genome-wide scans and in crossbreeding experiments with mouse, rat, pig, and chicken models; association and linkage studies with candidate genes and markers.

The current update includes reports that have dealt with an extended panel of phenotypes pertaining to obesity, including body mass index (BMI), percent body fat, fat mass, skinfold thicknesses, and fat free mass or phenotypes of leanness. Negative findings for candidate genes and markers are not incorporated in this version of the map but they are briefly mentioned when available to us.

In this year's review, we are using the nomenclature and gene symbols as defined by the HUGO Nomenclature Committee (6). As for chromosomal locations, we used the information from the Genome Data Base (7) and the Genetic Location Database (8).

Single Gene Mutations

  1. Top of page
  2. Abstract
  3. Introduction
  4. Single Gene Mutations
  5. Mendelian Disorders
  6. Quantitative Trait Loci (QTL) from Crossbreeding Experiments
  7. Association Studies
  8. Linkage Studies
  9. Conclusions
  10. Acknowledgments
  11. References

Because of significant progress in the characterization of the human genes first described in single-gene mutation rodent models and the recent study implicating Tubby in intracellular signaling by insulin (9), we have decided to reinstate the table describing these genes (Table 1). On the other hand, because progress in identifying specific genes involved in several of the syndromes related to obesity and the ever-expanding number of candidate genes potentially causing the disease, we have modified and updated the presentation of this section in this year's review. A section on single gene mutations will deal with syndromes in which obesity is clearly the dominant clinical feature (Table 2), whereas a Mendelian disorder section will review all syndromes found in the Online Mendelian Inheritance in Man (OMIM) database in which obesity or abnormal fat distribution is a related but nondominant clinical feature element (Table 3).

Table 1.  Single-gene mutation rodent models of obesity
 RodentHuman 
Mutations*ChrGenesInheritanceChrGenesGene productReferences
  • *

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

  • Chr: chromosome.

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

  • Status: October 1999.

Diabetes (db)4LeprRecessive1p31LEPRLeptin receptor(163,164)
Fat (fat)8CpeRecessive4q32CPECarboxypeptidase E(165)
Obese (ob)6LepRecessive7q31.3LEPLeptin(166)
Tubby (tub)7TubRecessive11p15.5TUBInsulin signaling protein(9,167,168)
Agouti yellow (Ay)2AyDominant20q11.2ASIPAgouti signaling protein(169)
Table 2.  Cases of human obesity caused by single-gene mutations
GeneLocationMutationParental statusSexAgeWeight (kg)BMI (kg/m2)Ref.
  1. NA = not available; M = mother; F = father; P = proband; S = sister; B = brother; N = niece; C = cousin; A = aunt; status of data shown is from October 1999.

LEPR1p31G[RIGHTWARDS ARROW]A (exon 16)P1916665.5(170)
   S1315971.5 
   S1913352.5 
POMC2p23G7013T & C7133Δ (exon 3)P330NA(171)
  C3804A (exon 2)P750NA 
PCSK15q15-q21Gly483ArgA[RIGHTWARDS ARROW]C+4 (intron 5)P336NA(172)
LEP7q31G398Δ (codon 133)P88645.8(173)
   C22936.6 
  C[RIGHTWARDS ARROW]T (codon 105) (exon 3)C6NA32.5(14)
   P22NA55.8 
   A34NA46.9 
   C3013054.9(15)
MC4R18q21.3ΔCTCT nt 631-634 (codon 211)P43228(174)
   F3013941 
   P20NA42.1(10)
   M43NA37.6 
  GATT insertion at nt 732 (codon 246)M58NA51(175)
   P35NA57 
   S34NA50 
   B24NA33 
   N11NA30 
  C105A (Tyr35X)P110NA31.3(10)
   P217NA45.9 
   M131NA48.2 
   M236NA38.6 
Table 3.  Obesity-related Mendelian disorders with known map location*
Mode of inheritanceOMIM no.SyndromeLocusCandidate geneRef.
  • *

    Adapted from OMIM (Online Mendelian Inheritance in Man) computerized data base (176); NA = not available. Status: October 1999.

Autosomal100800Achondroplasia (ACH)4p16.3FGFR3(39,42)
dominant103580Albright hereditary osteodystrophy (AHO)20q13.2GNAS1(17,27)
 103581Albright hereditary osteodystrophy 2 (AHO2)15qNA(28)
 105830Angelman syndrome with obesity (AGS)15q11-q13NA(45)
 147670Insulin resistance syndromes (IRS)19p13.3INSR(29,33)
 122000Posterior polymorphous corneal dystrophy (PPCD)20q11NANA
 151660Familial partial lipodystrophy Dunnigan (FPLD)1q21-q22NA(47)
 176270Prader-Willi syndrome (PWS)15q11-q13SNRPN(43,44)
 190160Thyroid hormone resistance syndrome (THRS)3p24.3THRB(37)
 181450Ulnar-mammary syndrome Schinzel syndrome or (UMS)12q23-24.1TBX3(46)
Autosomal203800Alstrom syndrome (ALMS1)2p13-p12NA(51)
recessive209901Bardet-Biedl syndrome 1 BBS111q13NANA
 209900Bardet-Biedl syndrome 2 BBS216q21NANA
 600151Bardet-Biedl syndrome 3 BBS33p13-p12NANA
 600374Bardet-Biedl syndrome 4 BBS415q22.3-23MYO9A(54)
 603650Bardet-Biedl syndrome 5 BBS52q31NA(52,53)
 269700Berardinelli-Seip congenital lipodystrophy (BSCL)9q34NA(48)
 216550Cohen syndrome (COH1)8q22-q23NANA
 212065Carbohydrate-deficient glycoprotein syndrome Type Ia (CDGS1A)16p13PMM2(49)
 227810Fanconi-Bickel syndrome (FBS)3q26.1-26.3SLC2A2(50)
X-linked301900Borjeson-Forssman-Lehmann syndrome (BFLS)Xq26.3FGF13(55)
 303110Choroideremia with deafness (CHOD)Xq21.1-21.2NANA
 300148Mehmo syndrome (MEHMO)Xp22.13-21.1NANA
 312870Simpson-Golabi-Behmel 1 (SGBS1)Xq26GPC3, GPC4(57,63)
  Simpson-Golabi-Behmel 2 (SGBS2)Xp22NA(56)
 309585Wilson-Turner syndrome (WTS)Xp21.1-q22NANA

Since last year's review, there have been very few new single gene cases published. The only major contribution has been by Hinney et al. who described six female obese subjects with mutations in the MC4R gene (10), two with the already known CTCT deletion at codon 211, and four others (two probands and their respective mothers) with a novel mutation at position 35 leading to a premature stop codon generating a truncated protein product. Seven missense mutations in MC4R of unknown significance in seven other extremely obese subjects (BMI > 99th percentile) were also described (10). Another group (11) reported on a 43-year-old woman with a BMI of 57 kg/m2, heterozygous for an Ile137Thr polymorphism in the MC4R gene, but with other carriers not showing obesity.

The Hinney group (10) also reported on a study for mutations in the POMC gene. One female subject (14.2 years old, BMI 32.2 kg/m2) was homozygous for a 9-basepair (bp) insertion between codons 73 and 74, whereas another female obese adolescent (aged 16.5 years, BMI 35.9 kg/m2) was a compound heterozygote for a 6-bp insertion at codon 176, and a G to T transversion at nucleotide (nt) 7316 together with a missense change A-7341-G. Finally, one obese subject (BMI 36.4 kg/m2) was heterozygous for an 18-bp insertion between codons 73 and 74. However, these polymorphisms were not demonstrated to be causative for the obesity observed among these subjects.

In two other genes, UCP3 and DRD4, polymorphisms have been reported with unclear clinical implications. In 1994, Nöthen et al. (12) found a male homozygous for a 13-bp deletion in exon 1 of the DRD4 gene, which causes a premature stop codon and probably a nonfunctional protein. The subject was obese (BMI 37 kg/m2 at age 50), had consistent slight hypothermia (rectal temperature of 35.4°C) and showed signs of autonomic hyperactivity with severe dermatography and excessive sweating, and left-sided acoustic neurinoma. In an association study on UCP3 gene polymorphisms in whites, Africans, and African-Americans, Argyropoulos et al. (13) reported that three obese subjects from the same family (aged 20, 14, and 11 with BMIs of 44.7, 29.2, and 26.1 kg/m2, respectively) were homozygotes for a missense change in exon 3 (Val102Ile). In another family, one compound heterozygote (age 16 and BMI of 51.8 with Type 2 diabetes mellitus) showing a stop codon in exon 4 (Arg143X) and a missplicing of exon 6 was also observed (13). Although the exon 6 polymorphism was associated with obesity and metabolic changes (see “Association Studies”), the demonstration that these variants are causative of a single gene mutation syndrome remains to be established.

The family of Turkish origin, showing a mutation in leptin gene (LEP) and already described by Strobel et al. in 1998 (14), was more thoroughly investigated by Ozata et al. (15), who found an additional female member carrying the same mutation. Of particular interest this year, a first case has been reported of specific treatment for a genetically caused obesity syndrome. In September 1999, Farooqi et al. (16) described the significant clinical response to recombinant human leptin in a 9-year-old girl with severe obesity and congenital leptin deficiency. Over a 12-month period, the patient lost 16.4 kg of body weight of which 15.6 kg were fat mass (baseline body weight of 94.4 kg and BMI of 48.2 kg/m2).

Mendelian Disorders

  1. Top of page
  2. Abstract
  3. Introduction
  4. Single Gene Mutations
  5. Mendelian Disorders
  6. Quantitative Trait Loci (QTL) from Crossbreeding Experiments
  7. Association Studies
  8. Linkage Studies
  9. Conclusions
  10. Acknowledgments
  11. References

In this year's review, we are expanding this section with the inclusion of several new syndromes in which obesity or fat distribution anomalies are part of the clinical synopsis in the OMIM database, and for which chromosomal locations are known (Table 3). We have also added information on the most likely candidate gene polymorphisms and mutations for the syndromes when available.

Among the autosomal dominant diseases, there are three new additions to the summary table (Table 3). Albright's hereditary osteodystrophy (AHO) is characterized by obesity, rounded facies, short stature, and subcutaneous calcifications. Two phenotypical variants exist. One is pseudohypoparathyroidism (PHP) where hypocalcemia and hyperphosphatemia refractory to exogeneous parathyroid hormone (PTH) are present, owing to peripheral resistance to PTH (other hormone resistance conditions often also exist). The less severe form is pseudopseudohypoparathyroidism (PPHP), where no biochemical anomaly is observed. The disease is caused by reduced expression or altered function of the alpha-subunit of the Gs protein that couples receptors to adenylyl cyclase stimulation. A whole series of variations in the gene encoding this protein, GNAS1, have been reported: in exon 1 (17, 18), exon 4 (19), intron 5 (20), exons 7–8 (19, 21), exon 9 (22), intron-exon 10 (23, 24, 25), and exon 13 (26, 27). Also, in one study AHO was linked to markers on chromosome 15q11 (28), defining the new subtype AHO2.

In the family of hereditary insulin resistance syndromes (IRS), there is Type C IRS in which obesity accompanies hyperandrogenism, insulin resistance, and acanthosis negricans (HAIR-AN syndrome) in the absence of autoimmunity. This type differs from Type A IRS where obesity is absent, but overlaps with the polycystic ovary syndrome (PCOS) in which the same clinical features are present. Many mutations in the gene encoding the insulin receptor (INSR) have been described in IRS but most have been found in subjects with forms other than Type C or in nonobese subjects. However, some studies reported variations in clearly obese subjects: an exon 3 deletion (29), an exon 14 deletion (30, 31), and mutations in exon 20 (32, 33). On the other hand, several reports have failed to find mutations in the INSR gene in IRS Type C patients (34, 35, 36).

The last addition is the thyroid hormone resistance syndrome (THRS), where a mutation in the THRB gene was reported by Behr et al. in 1997 (37). We now include this case in the present section because obesity was not the dominant feature of the patient.

For the other autosomal dominant syndromes, several advances have occurred. In achondroplasia, the most common genetic form of dwarfism in which obesity is highly prevalent (38), the causal gene was reported to be fibroblast growth factor receptor 3 (FGFR3) (39, 40, 41, 42). Almost all patients have a G to A transition or G to C transversion at nt 1138.

In the Prader-Willi syndrome, most patients have 3- to 4-megabase (Mb) deletions in the paternally derived chromosome at 15q11.2, and most of the remainder have maternal disomy, i.e., two maternally derived chromosomal regions at 15q11. However, a small number of patients have microdeletions in the imprinting center at 15q11-q13. Two groups (43, 44) recently narrowed down the location of the latter causal defects to a critical region of less than 4.3 kb spanning the promoter and exon 1 of the small nucleoriboprotein N (SNRPN) gene, or the exons 2 and 3 of the same gene. A new form of Angelman syndrome with obesity was described this year by Gillessen-Kaesbach et al. (45). The syndrome, characterized by muscular hypotonia and mild mental retardation, is caused by an imprinting defect in the same chromosomal region as the PWS, at 15q11-q12.

For the ulnar-mammary syndrome (UMS), mutations in exons 1 and 2 of the TBX3 gene were found in 1997 in families with members presenting the syndrome (46). Finally, a new linkage study in white Germans confirmed the linkage of familial partial lipodystrophy to chromosome 1q21-q22, with a multipoint lod score of 6.27 near marker D1S2721 (47).

In the autosomal recessive disease category, three syndromes have been added. The Berardinelli-Seip syndrome is a rare disorder characterized by a near complete absence of adipose tissue. Subjects are highly insulin resistant, hypertriglyceridemic, with acanthosis negricans and Type 2 diabetes mellitus at a young age. A recent study in families of various ethnic backgrounds found linkage to loci D9S1818 and D9S1826, with a maximal Lod score of 5.4 (48).

The carbohydrate-deficient glycoprotein syndrome type 1A (CDGS1A) or Jaeken syndrome is caused by defective glycosylation of glycoconjugates resulting in severe encephalopathy with axial hypotonia, abnormal eye movements, psychomotor retardation, peripheral neuropathy, cerebellar hypoplasia, retinosis pigmentosa, nipple retraction, hypogonadism, and lipodystrophy. One group reported in 1997 on 11 different missense mutations in the human phosphomannomutase 2 (PMM2) gene, found only in the affected subjects (49).

In the Fanconi-Beckel syndrome (FBS), patients have sparse subcutaneous fat as well as hepatorenal glycogen accumulation due to impaired utilization of glucose and galactose. Mutations in exons 3, 6, and 8 of the SLC2A2 gene that encodes the facilitative glucose transporter 2 were found by Santer et al. (50).

New results were published on Alstrom syndrome, where the causal region was narrowed down to a 6.1-cM interval between D2S291 and D2S2114 on chromosome 2 in a linkage study performed on a consanguineous pedigree of North African origin (51). In the Bardet-Biedl syndrome, a fifth locus was mapped to 2q31 in a Newfoundland pedigree (52, 53) and the unconventional myosin IXA (MYO9A) gene was investigated with inconclusive results in a study on BBS4 families (54).

The last category deals with X-linked diseases. No new syndrome has been reported in this category. For the Borjeson-Forssman-Lehmann syndrome, the fibroblast growth factor 13 (FGF13) gene, previously named fibroblast growth homologous factor 2, was characterized and mapped to the same Xq26 location as the syndrome, but its role remains to be explored (55). In the Simpson-Golabi-Behmel syndrome (SGBS), a new chromosomal region was mapped, at Xp22, in a severely affected family (56). Moreover, deletions have been reported in several exonic areas of the glypican-3 and glypican-4 (GPC3 and GPC4) genes located side by side at Xq26, in SGBS families (57, 58, 59, 60, 61, 62) and several of these were summarized in 1998 by Neri et al. (63).

Quantitative Trait Loci (QTL) from Crossbreeding Experiments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Single Gene Mutations
  5. Mendelian Disorders
  6. Quantitative Trait Loci (QTL) from Crossbreeding Experiments
  7. Association Studies
  8. Linkage Studies
  9. Conclusions
  10. Acknowledgments
  11. References

The number of animal QTLs linked to body weight or body fat has increased by 25 since the last review (Table 4). Five QTLs linked to energy expenditure in mice, and one QTL to food intake in chickens have also been reported. A total of 98 animal QTLs have now been evidenced and their equivalent syntenic regions in humans, when they can be determined with available maps, are shown in Table 4. We have proposed acronyms for QTLs to facilitate their inclusion in the map when none was provided by the authors. Overall, the results of five mouse, three rat, three pig, and one chicken novel crosses have been published. Some existing mouse and pig crosses have been further investigated as well.

Table 4.  QTLs reported for animal polygenic models of obesity with their putative syntenic locations in the human genome*
     Chromosomes 
Crosses QTLStatisticPhenotypesAnimalHumanReferences
  • *

    Synteny relationships established according to References 84,85,86,87,88.

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

  • Also observed in the CAST/Ei x C57B1/6J F2 intercross (193).

  • §

    Also observed in the cross (C3H/He x A/J) x M. spretus (65).

  • 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 = non-insulin dependent diabetes/Goto-Kakizaki; bw/gk = body weight/Goto-Kakizaki; Niddm = non-insulin dependent diabetes mellitus. Hlq = heat loss QTL; Fatq = fat QTL; Batq = brown adipose tissue QTL; Pfatp = predicted fat percent; Dmo = diabetic mouse; SHR = salt hypertensive rat; SSC = swine carcass; AFIFA = avian feed intake at a fixed age interval. NA = not available. Status: October 1999.

MouseM. spretus xMob1Lod = 4.26.5% percent fat716p12.1-p11.2(177)
 C57BL/6JMob2Lod = 4.87.1% femoral fat67q22-q31.3 
  Mob3Lod = 4.87.0% percent fat1214q31-q32 
  Mob4Lod = 3.45.9% mesenteric fat155p13 
MouseNZB/B1NJ x SM/JMob5Lod = 3.636% body fat220q12-q13(178)
MouseCAST/Ei xMob6Lod = 7.3Subcutaneous fat22q31-q37(179)
 C57BL/6JMob7Lod = 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 x SWR/JDob1Lod = 4.5NA41p36.13-p35(180)
      9p13 
  Dob2Lod = 4.87% adiposity93p21(181)
  Dob3Lod = 3.94% adiposity158q23-q24 
MouseA/J x M. spretusBw1§Lod = 3.424% body weightXXp11-q26(65)
 x C57BL/6JBw2§Lod = 6.6(3 QTLs together)XXq11-q13 
  Bw3Lod = 4.3 XXp22-q27 
MouseJU/CBA x CFLP (P6 line)QbwXLod = 24.417–20% 10 weeks weightXXq26.3-q27.2(64)
MouseDu6 x DuKQbw1Lod = 2.76.9% abdominal fat31p22-p21(182)
      4q23-q25 
  Qbw2Lod = 7.617% body mass1117q12-q22 
MouseDu6 x DukBw4F = 4.7923.1% body weight1117p13-q23(183)
  Afw1/Afp1F = 4.8910–13% abdominal fat41p36-q33 
      9p21-p13 
  Afw2F = 4.798.3% abdominal fat112p23-p12 
      5q21-q34 
      7p13-p12 
      16p13 
      22q12 
  Afw3F = 4.707.7% abdominal fat131q41-q43 
      7p15-p13 
  Afp2F = 4.898.3% abdominal fat (%)31p36-q31 
      3q21-q27 
      4q21-q32 
Mouse129/Sv x Le/SuzObq1Lod = 8.012.3% adiposity719q13.2-q13.3(184)
  Obq2Lod = 5.56.3% adiposity 1q21-q23 
      2q35-q36.1 
MouseAKR/J x C57L/JObq3Lod = 5.17.0% adiposity22q23-q31(185)
      9q32-q34 
      11p12-p11 
      15q13-q14 
      20pter-p11 
      20q11 
  Obq4Lod = 4.66.1% adiposity176q25-q27 
MouseKK/H1Lt xObq5Lod = 6.317% adiposity (females) 911q22-q24(66)
 C57BL/6JObq6Lod = 5.011.7% adiposity (males)XXq26-q28 
  KK7Lod = 6.9/4.4Body weight/inguinal fat 711q21 
        
MouseKK-A(y) xBwq1Lod = 3.115% body weight 4NA(67)
 C57BL/6JBwq2Lod = 3.4/4.119% body weight/26% 63p25 
    Adiposity 12p13 
      6p21 
MouseTSOD x BALB/cANidd5Lod = 5.9110.9% body weight 22q23-q37(68)
  Nidd6Lod = 4.659.2% body weight 11q25-q41 
MouseM16i x CAST/EiPfat1NAAdiposity 22p13-q21(186)
      15q11-qter 
      20pter-p11 
  Pfat2NAAdiposity 220qcen-q11 
  Pfat3NAAdiposity135q11-q14 
      5q33-qter 
      6p23 
      9q21-q22 
  Pfat4NAAdiposity155p14-p12 
      8q22-q24 
  Pfat5NAAdiposity158q21-qter 
      22q12-qter 
MouseDBA/2J xHlq1Lod = 5.64.7% heat loss 11q21-q41(72)
 C57BL/6JHlq2Lod = 3.73.1% heat loss 211p14-p11 
      5q11-q21 
  Hlq3/4Lod = 3.8/4.73.1/3.9% heat loss 31p21-p13 
      3q21-q26 
  Hlq5Lod = 4.063.4% heat loss 74q28-q31 
      10q24-q26 
      11q13-q14 
  Fatq1Lod = 7.955.9% gonadal fat 116p13-p11 
  Batq1Lod = 3.963.3% brown fat 118q21.3-q22.1 
  Batq2Lod = 3.462.8% brown fat 31q41-q42.1 
      4q28-q31 
MouseDBA/2J xBw6aLod = 3.33% 6 weeks weight 11q31-q33 (70)
 C57BL/6JBw6bLod = 3.34% 6 weeks weight 49p24-p23 
  Bw6cLod = 3.24% 6 weeks weight 54q12-q13 
  Bw6dLod = 4.35% 6 weeks weight 512q24 
  Bw6eLod = 4.04% 6 weeks weight 62p12 
  Bw6fLod = 6.99% 6 weeks weight 715q11-q13 
      19q13 
  Bw6gLod = 4.45% 6 weeks weight 96q12-q16 
  Bw6hLod = 5.76% 6 weeks weight1117p13 
  Bw6iLod = 4.14% 6 weeks weight1315q23-q25 
  Bw6jLod = 3.03% 6 weeks weight143p21 
      10q22-q24 
      13q14-q22 
      21pter-qter 
  Bw6kLod = 4.97% 6 weeks weight176p21 
MouseDBA/2J xPfatp4Lod = 5.020% predicted fat (%)  49p24(71)
 C57BL/6JPfatp6Lod = 4.9(4 QTLs together) 63p14.1-p12 
  Pfatp13Lod = 5.3 135q22-q31 
  Pfatp15Lod = 8.6 158q24-qter 
MouseQuackenbush-Swiss x C57BL/6JQsbwp < 0.00940% body weight1012q22-q23(187)
MouseLG/J x SM/JQlw1Lod = 2.31.9% late weight gain 12q11-q12(188)
      6p12-p11 
  Qlw2Lod = 2.92.6% late weight gain 220p11 
      20q11 
  Qlw3Lod = 2.38.4% late weight gain 33q25-q26 
  Qlw4Lod = 2.42.4% late weight gain 46q16 
      8q11-q12 
  Qlw5Lod = 2.83.4% late weight gain 63p26-p24 
  Qlw7Lod = 2.02.0% late weight gain 715q26 
  Qlw9Lod = 2.52.4% late weight gain 911q21 
      19p13 
  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 
      13q12 
  Qlw18Lod = 1.63.0% late weight gain185q31-q33 
MouseNSY x C3H/HeNidd3nsyLod = 6.75Epididimal fat 612p(69)
      2p13-p12 
      3q21 
      17q23 
RatLeprfa/Leprfa 13M xQfa1Lod = 2.35.4% weight (male) 116q13(189)
 WKY Lod = 2.55.8% BMI (male) 16p11 
   Lod = 2.26.9% BMI (female) 11p15 
      11q13 
  Qfa12Lod = 2.77.8% weight (female)127q22 
   Lod = 3.08.3% BMI (female)   
RatGK x BNNidd/gk1NA13% adiposity 13p21(190)
  Nidd/gk5NA9% body weight 811q22-q23 
  Nidd/gk6NA7% body weight171q41-q44 
  bw/gk1NA24% body weight 78q21-q24 
      22q12-q13 
RatGK x FNiddm1Lod = 3.223.5% body weight 110q24-q26(191)
  Niddm3Lod = 3.0NA1017pter-q23 
  Weight1Lod = 6.2NA 712q22-q23 
RatOLETF x BNDmo1Lod = 6.011.6% body weight 110q23-q24(73)
RatDahl x MNSDAHL3p < 0.0000313% body weight 310q25(74)
RatSHR x BB/OKSHR1Lod = 3.332% body weight (males) 111p15.5(75)
  SHR4Lod = 3.114% body weight (females) 47p15.3 
PigEuropean wild boar xFAT1NANA 41q21-q25(76)
 Large White F = 15.8/18.6back/abdominal fat  (77)
   p < 0.000115.4% visceral fat  (78)
   p < 0.00017.3% subcutaneous fat   
   p < 0.00019.7% body fat (%)   
PigMeishan x Large WhiteBFM4NAmidback fat depth 41q21-q25(79)
PigWild boar x Large WhiteIGF2qF = 7.110.4% backfat depth 2p11p15.5(80)
PigMeishan x DurocPig QTL2p < 0.01average backfat 76p21(192)
 Meishan x Hampshire      
 Meishan x Landrace      
 Minghu x Hampshire      
 Minghu x Landrace      
PigMeishan x LandraceSSC7F = 18.0backfat thickness 76p21.3(81)
 Minghu x Large White    15q22-qter 
PigMeishan x WhiteSSC1F = 15.4Backfat thickness 19q32-q34.1(82)
 compositeSSC7F = 14.7Backfat thickness 76p21.3 
  SSCXF = 32.3Backfat thicknessXX 
ChickenWhite Plymouth Rock x White Plymouth RockAFIFA12.8Food intake 1NA(83)

From the mouse cross JU/CBA x CFLP (P6 line), originally selected for growth rate, a strong QTL explaining 17% to 20% of the body weight at 10 weeks was observed on the X chromosome (QbwX; [(64)]). It could correspond to the previously described QTL Bw3 of Dragani et al. (65). Four mouse crosses involving diabetic strains have been reported. Taylor et al. (66) have produced a new cross between the diabetic KK/H1Lt and the C57BL/6J strains and identified two QTLs related to adiposity, in females (Obq5) or males (Obq6), and a third to body weight and inguinal fat (KK7). Suto et al. (67) from the cross KK-A(y) (diabetic) x C57BL/6J have detected a QTL related to body weight (Bwq1) and to body weight and adiposity (Bwq2), whereas two QTLs (Nidd5 and Nidd6) related to body weight were observed from the cross involving the diabetic TSOD and BALB/cA strains (68). Finally, in the cross NSY (diabetic) x C3H/He, a QTL (Nidd3nsy) related to epidydimal fat weight was observed (69).

From the cross C57BL/6J x DBA/2J, previously characterized for body weight at 6 weeks (70), four new QTLs related to percent fat predicted from body weight and dry weight carcass, have been uncovered (Pfatp4, Pfatp6, Pfatp13, and Pfatp15 [(71)]). In an experiment using C57BL/6J x DBA/2J, QTLs for energy expenditure were investigated using the heat loss measured in a metabolic chamber as the phenotype (72). Five QTLs (Hlq1 to Hlq5) were uncovered with heat loss, one with gonadal fat pad (Fatq1), and two with brown fat levels (Batq1 and Batq2 [(72)]).

One new rat cross involved the diabetic OLETF and the BN strains, and two between the hypertensive strains Dahl or SHR with the Milan normotensive (MNS) and BB/OK strains, respectively, have been produced. QTLs with body weight were observed from the OLETF (Dmo1 [(73)]), the Dahl (DAHL3 [(74)]), and the SHR (SHR1 and SHR4 [(75)]) crosses.

The first QTLs reported in pigs from the cross between European wild boar x Large white (76) have been confirmed in additional studies using a similar cross, with back and abdominal fat (77), and with visceral, abdominal, and percent fat (FAT1 [(78)]). Moreover, this QTL was also observed in the different cross Meishan x Large white (79). On the other hand, a new QTL with backfat depth and possibly involving the insulin-like growth factor 2 (IGF2) gene, has been uncovered in a Wild boar x Large white cross (80). Finally, three QTLs with backfat thicknesses have been uncovered in a Meishan x Landrace and a Minghu x Large White crosses (SSC7 [(81)]), and a Meishan x White composite (SSC1, SSC7, and SSCX [(82)]). As to the chicken, a first QTL related to food intake has been observed in a cross between different strains from White Plymouth Rock stocks (AFIFA1 [(83)]).

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, according to the Mouse Genome Database (MGB) from the Jackson Laboratory (84), of the markers defining the QTL, was compared to the equivalent region in the human genome using the integrated linkage maps of the Mouse/Human homology maps (85). For the rat, maps described in Yamada et al. (86) and Jacob et al. (87) were used, whereas the map from the Animal Genome Database in Japan (88) was used for the pig. No information was found for the chicken.

Association Studies

  1. Top of page
  2. Abstract
  3. Introduction
  4. Single Gene Mutations
  5. Mendelian Disorders
  6. Quantitative Trait Loci (QTL) from Crossbreeding Experiments
  7. Association Studies
  8. Linkage Studies
  9. Conclusions
  10. Acknowledgments
  11. References

The evidence for association between candidate genes and obesity-related phenotypes is summarized in Table 5. Studies published over the past year have shown associations of BMI and body weight with polymorphisms in UCP2 and UCP3 (13, 89, 90), PPARG (91, 92, 93), ADRB2 (94, 95, 96, 97), APOA4 (98), CD36L1 (99), IRS1 (100), GNB3 (101, 102, 103), and ADA (104). Fat mass and/or percent body fat were associated with markers of ADRB3 (105), IGF1 (106), and AGT (107), whereas fat-free mass showed associations with LEPR (108) and UCP1 (106). In addition, the PON2 gene has been reported to be associated with birth weight (109). Changes in BMI and body weight have been associated with variation in the PPARG (110), IRS1 (100), and UCP1 (111) genes. Weight gain during pregnancy was associated with the ADRB3 gene polymorphism (112). Plasma leptin levels have also found to be associated with variation in the POMC (113) and the IRS1 (114) genes. Basal metabolic rate has been reported to be associated with the ADRA2B gene (115) and positive associations were found between respiratory quotient and markers of the ATP1A2 (116) and the UCP3 (13) genes. Finally, a UCP2 gene polymorphism was associated with 24-hour energy expenditure, spontaneous physical activity, non-protein respiratory quotient, and fat oxidation (117).

Table 5.  Evidence for the presence of an association between markers of candidate genes with BMI, body fat, and other obesity-related phenotypes
GeneLocationN casesPhenotypep valueReference
  1. SF = skinfolds; FFM = fat free mass; RQ = respiratory quotient; WHR = waist-to-hip ratio; FM = fat mass; BMI = body mass index; WC = waist circumference; HC = hip circumference; SPA = spontaneous physical activity; NPRQ = non protein RQ; LBM = lean body mass. Status: October 1999.

HSD3B11p13.113212-year changes in σ 6 SF0.04 (194)
LEPR1p3120%fat0.003(195)
  308FFM in subjects with BMI ≥ 270.03–0.05(108)
  130Extreme obesity in children0.02–0.04(196)
ATP1A21q21-q23122%fat, RQ<0.05  (197)
  156RQ in young adults 0.0001(116)
AGT1q42-q43316WHR0.007(198)
  94FM in women ≥ 42 years0.008–0.02 (107)
ACP12p2575BMI in children0.02 (199)
  265BMI in type 2 subjects0.002(200)
APOB2p24-p23232BMI0.005(201)
  181BMI0.05 (202)
  56%fat, abdominal fat0.04 (203)
POMC2p23337Leptin in Mexican Americans0.001(113)
ADRA2B2p13-q13166Basal metabolic rate in obese non-diabetics0.01 (115)
IRS12q361748Current BMI and ΔBMI since age 25 in African Americans0.04–0.05(100)
  156Leptin in obese subjects0.03 (114)
PPARG3p25820Leptin in obese subjects0.001(204)
  333BMI in middle-aged0.03 (91)
  973BMI in elderly0.02  
  752ΔBMI in obese men0.002–0.008(110)
  869ΔBMI in lean men  
  121BMI0.03 (92)
  141Weight, BMI, LBM, FM, waist, and hip girths0.002–0.05 (93)
APOD3q27-qter114BMI0.006(205)
FABP24q28-q31395Abdominal fat0.008(206)
  507BMI, %fat0.01 (207)
UCP14q28-q31123High fat gainers over 12 years0.05 (208)
  163Weight and BMI loss<0.05  (209)
  113Weight loss in Japanese women0.001(111)
GRL5q31-q3251Abdominal visceral fat in lean subjects0.003 < p < 0.007(210)
ADRB25q31-q32140BMI, FM, fat cell volume0.001 < p < 0.009(211)
  508BMI in Japanese subjects0.001(94)
  836Body weight, BMI, WC, HC, WHR in sedentary French men<0.002 (95)
  574BMI in Japanese subjects0.009–0.003(96)
  277BMI in Japanese men0.004(97)
TNFA6p21.338%fat0.02(212)
  363BMI0.01(213)
  1351BMI0.004(214)
GCK7p15-p1358Birth weight0.002(215)
PON27q21.3100Birth weight in Trinidadian with South Asian origin<0.05(109)
LEP D7S2519, 649,7q31.3168Weight loss0.006 < p < 0.007(216)
530, 1875 84Weight0.05(217)
  395Leptin0.02(218)
  117Leptin0.04(219)
   Leptin response to diet0.005 
  103Weight<0.05(220)
LPL8p22236BMI (leanness)0.05(221)
ADRB38p12-p11.2128Weight gain over 25 years0.01(222)
  185Weight gain over 20 years, current weight0.007 < p < 0.03(223)
  335WHR in women0.02(224)
  350BMI0.009(225)
  49BMI0.03(226)
  295BMI<0.05(227)
  254Early onset obesity0.002(228)
  131Abdominal visceral fat, FM<0.01(229)
  398Visceral/subcutaneous abdominal fat, BMI0.02 < p < 0.03(230)
  83BMI in CAD patients<0.05(231)
  53Obesity<0.05(232)
  586BMI, HC in women<0.03(233)
  56BMI, FM, WC<0.05(234)
  261BMI<0.05(235)
  211Moderate obesity0.02(236)
  179ΔBMI during pregnancy0.006–0.02(112)
  76FM in Thai males<0.05(105)
CBFA2T18q22281%FAT, BMI, WC, HC0.0002 < p < 0.02(237)
ADRA2A10q2572Trunk to extremity SF ratio0.002(238)
SUR11p15.1232Morbid obesity0.02(239)
IGF211p15.51474BMI0.02(240)
INS11p15.5758Birth weight0.009(241)
  52WHR in obese women0.005(242)
UCP211q1382Sleeping and 24-hour metabolic rate0.007 < p < 0.04(243)
  790BMI in subjects > 45 years0.04 
  220BMI in South Indian women0.02(89)
  143BMI in South Indian parents of type 2 probands<0.001 
  6024-hour energy expenditure, 24-hour SPA, sleeping SPA, 24-hour NPRQ, 24-hour fat oxidation0.005–0.05(117)
UCP311q13120BMI, RQ, NPRQ, fat oxidation/LBM in African Americans0.008–0.04(13)
  382BMI, maximal BMI, and weight during diet therapy in morbidly obese patients0.02–0.04(90)
APOA411q23375BMI and WHR in young men without family history of MI0.004(98)
DRD211q22.2-q22.3392Relative weight0.002(244)
GNB312p13197BMI in hypertensives0.02(101)
  1950Weight and BMI in young white, Chinese, and black African males0.001–0.05(102)
  213BMI, waist and hip girths, and SF in Nunavut Inuit<0.05(103)
IGF112q22-q23502FM, %FAT, FFM, ΔFMM after 20-week endurance training<0.05(106)
    0.005 
CD36L112q24288BMI in healthy lean women0.004–0.03(99)
MC5R18p11.2156BMI in females0.003(245)
MC4R18q21.3156FM, %FAT, FFM in females0.002 < p < 0.004(245)
INSR19p13.375Obesity (BMI > 26) in hypertensives0.05(246)
LDLR19p13.284BMI in hypertensives0.004(247)
  112BMI in hypertensives0.04(248)
  83BMI in normotensives0.008(249)
  270Obesity (BMI ≥ 26)0.02(250)
LIPE19q13.1-q13.2380Obesity0.002(251)
GYS119q13.3130Obesity0.03(252)
ADA20q13.12273BMI in type 2 subjects0.0004–0.01(104)

In addition to the simple associations between obesity-related phenotypes and individual gene markers, some studies tested for gene-environment and gene-gene interactions. In a large cohort of men from northern France, highly significant associations between body weight, BMI, waist and hip circumferences, and the Gln27Glu polymorphism of the ADRB2 gene were observed in sedentary men but not in those who were physically active (95). Additive effects of polymorphisms in the UCP1 and ADRB3 genes on weight loss were reported in obese Japanese (111) and Finnish (118) women. Moreover, data from the Atherosclerosis Risk in Communities Study cohort suggest that there is an interaction effect between the IRS1 and FABP2 gene variants on BMI (100).

In addition to the 89 studies with positive findings summarized in Table 5, we uncovered 35 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 (ten studies) (119, 120, 121, 122, 123, 124, 125, 126, 127, 128), PPARG (three studies) (129, 130, 131), and LEP (three studies) (132, 133, 134). Other markers yielding negative findings were related to POMC (135, 136); MC4R (11, 137); UCP1 (138, 139); UCP2 (140); UCP3 (141); ADRB2 (142, 143); HTR1B and HTR7 (144); CNTF (145); IRSI (146); CCKAR (139); FABP2 (147); NPY (148); ESR2 (149); GLP1R, ASIP, and MC5R (137); TNFA (150); and the mitochondrial DNA D-loop region (151).

Linkage Studies

  1. Top of page
  2. Abstract
  3. Introduction
  4. Single Gene Mutations
  5. Mendelian Disorders
  6. Quantitative Trait Loci (QTL) from Crossbreeding Experiments
  7. Association Studies
  8. Linkage Studies
  9. Conclusions
  10. Acknowledgments
  11. References

Table 6 presents a summary of the studies providing evidence of linkage with obesity-related phenotypes. The results of two other genome-wide scans performed in French (152) and American (153) families became available, adding to those already reported in Pima Indians (154, 155, 156) and in Mexican-Americans (157). In order to distinguish linkages from genomic scans and markers not surrounding known candidate genes, we used “QTL” in the gene column, and indicated the name of the markers closest to the QTL. One of them was performed on 158 nuclear families from Paris-Lille (152), using a total of 380 microsatellite markers with an average distance between markers of 9.1 cM (range 1.5 to 28.8 cM). The strongest evidence of linkage with obesity (BMI > 27 kg/m2) was found on chromosome 10p with a maximum Lod score value of 4.85 near markers D10S197 and D10S611. Additional evidence of linkage was found with plasma leptin levels at 2p21 (Lod = 2.68 with markers D2S165 and D2S367) and 5q (Lod = 2.93 with marker D5S426). Another genome-wide scan was reported based on 513 individuals from 92 families ascertained through an extremely obese proband (BMI ≥ 40 kg/m2), with the addition of 32 families for the mapping of the region providing the most promising evidence of linkage (153). A total of 354 microsatellite markers, on average 10.1 cM apart, were genotyped and tested for linkage with BMI and percent body fat measured by bioelectric impedance. Significant evidence of linkage using single-point and multipoint methods was found on chromosome 20q13 near markers D20S107, D20S211, and D20S149 (153).

Table 6.  Evidence for the presence of linkage with obesity-related phenotypes
GeneMarkersLocationN pairsPhenotypesp or Lod valueReference
  1. RQ = respiratory quotient; BMI = body mass index; RMR = resting metabolic rate; TER = trunk to extremity skinfolds ratio; WHR = waist to hip circumferences ratio; SF = skinfold; FM = fat mass; FFM = fat free mass; WC = waist circumference; HC = hip circumference; FPL = familial partial lipodystrophy. Status: October 1999.

PGD 1p36.2-p36.13>168Suprailiac SFp = 0.03(253)
QTLD1S193, 200, 4761p35-p31202–251BMI, σ6 SF, FM0.009 < p < 0.02(254)
LEPRQ223R, CA (IVS 3), CTTT (IVS 16)1p31268–324BMI, σ6 SF, FM, FFM0.005 < p < 0.05(108)
QTLD1S5501p31-p2123624-hour RQLod = 2.8(156)
QTLD1S4981q219 affected/53FPLLod = 6.9(255)
 D1S26241q21-q2215 affected/53FPLLod = 5.8(256)
ATP1B1 1q22-q2594RQp = 0.04(197)
ATP1A2 1q22-q25289RQp = 0.02(116)
ACP1 2p25>300BMIp = 0.004(257)
   >168Triceps SFp = 0.02(253)
QTLD2S17882p21>5000 relative pairsLeptin, FMLod = 4.9/2.8(157)
   720 subjects; 230 familiesLeptin, BMI0.008 < p < 0.03(158)
   337 individualsLeptinLod = 7.5(113)
QTLD2S165, 3672p22-p21264LeptinLod = 2.4/2.7(152)
IGKC 2p12>168Triceps SFp = 0.03(253)
QTLD3S24323p24.2-p22377% fatLod = 2.0(155)
GYPA 4q28-q31160TERp = 0.02(258)
QTLD5S4265p11264LeptinLod = 2.9(152)
ISL1 5q22.3226Obesityp = 0.03(160)
   284BMI, Leptin0.0004 < p < 0.006 
GRL 5q31-q3288BMI > 27p = 0.009(259)
ADRB2 5q31-q3266TERp = 0.02(238)
BF 6p21.3>168Triceps, subscapular, suprailiac SF0.01 < p < 0.03(253)
TNFATNFir24, D6S273, 2916p21.3>255% fat0.002 < p < 0.05(213)
GLO1 6p21.2-p21.1>168Suprailiac SF, relative weight0.004 < p < 0.05(253)
NPY 7p15.1545Principal component of height, weight, SF, abdominal and HCp = 0.05(161)
   170Obesityp = 0.04 
LEP 7q31.347Body fatp = 0.008(260)
 D7S680, 514, 530 60BMI > 350.002 < p < 0.009(261)
 D7S504, 1875 59BMI ≥ 40p = 0.04(262)
   88BMIp = 0.04(263)
 D7S504 46BMI > 85th percentilep = 0.001(264)
 D7S514, 495 545BMI, SF, fat, WC0.0001 < p < 0.02(265)
 D7S1875 545WHRp = 0.009(161)
KEL 7q33402BMI, σ6 SF<0.0001(258)
    TER0.04 
ADRB3D8S11218p12-p11.2470 subjects from 10 large pedigreesBMILod = 3.2(159)
QTLD8S11108q11.1>5000 relative pairsLeptinLod = 2.2(157)
ORM1 9q32>168Suprailiac SFp = 0.03(253)
AK1 9q34.1>168Suprailiac SFp = 0.01(253)
QTLD10S19710p12.3264ObesityLod = 4.9(152)
SURD11S41911p15.167BMI ≥ 27p = 0.003(239)
CCKBR 11p15.4221Leptinp = 0.01(160)
UCP2/UCP3 11q13240 relative pairsRMRp = 0.000002(266)
QTLD11S2000, 236611q22277% fatLod = 2.8(155)
 D11S2366 451% fatLod = 2.1(156)
QTLD11S97611q2323624-hour energy exposureLod = 2.0(156)
QTLD11S91211q241766BMILod = 3.6(154)
IGF1 12q22-q23352Visceral fatp = 0.02(106)
ESD 13q14.1-q14.2194σ6 SF, %fatp < 0.04(258)
MC5R 18p11.2242–289BMI, σ6 SF, FM, %fat, FFM, RMR0.001 < p < 0.02(245)
MC4R 18q21.3210RQp = 0.04(245)
   105Obesity0.001 < p < 0.003(162)
QTLD18S87718q21451% FATLod = 2.3(156)
ADA 20q13.12428BMI, σ6 SF0.02 < p < 0.001(258)
 ADA, D20S17, 12020q12-q13139–226BMI, σ6 SF, FM, %fat0.004 < p < 0.02(178)
MC3R 20q13.32212–258BMI, σ6 SF, FM0.008 < p < 0.02(178)
QTLD20S60120q11.223624-hour RQLod = 3.0(156)
QTLD20S107, 211, 14920q13423BMI > 30, %fat3.0 < Lod < 3.2(153)
P1 22q11.2-qter>168relative weightp = 0.03(253)

The evidence of linkage previously reported with plasma leptin in Mexican-Americans on 2p21 (157) was substantially increased (Lod = 7.46) by typing six additional markers (113) and replicated in African-American families with marker D2S1788 (158) and in the genomic scan of the Paris-Lille families (152). Another linkage study performed in Mexican-Americans with markers surrounding the ADRB3 locus found significant evidence of linkage (Lod = 3.21) with BMI between D8S1121 and the ADRB3 gene (Trp64Arg polymorphism), some 2.5 cM telomeric to the ADRB3 locus (159). In a sib-pair linkage study of 15 candidate genes of food intake regulation, glucose and insulin metabolism, energy expenditure, and adipose tissue metabolism performed in French families with morbid obesity (160), significant evidence of linkage was found between the LIM/homeodomain islet-1 (ILS1) gene on 5q and obesity (p = 0.03), BMI (p = 0.001), and leptin levels (p = 0.0003), as well as between the CCKBR gene and plasma leptin (p = 0.01). All the other genes tested (ADRB3, UCP1, PPARG, LIPE, LPL, APOC2, TNFA, CCKAR, GLP1R, FABP2, CDX3, IRS1, and CPT1) yielded negative findings (160). In a similar study involving polymorphisms within or near seven candidate genes of obesity typed in 302 subjects from 59 Mexican-American families (161), weak evidence of linkage (p = 0.048) was found between a marker (D7S2190) located within 200 kb of the NPY gene and a composite variable obtained by a principal component analysis of body weight and anthropometric measures, and between a marker located within 290 kb of the LEP gene and waist-to-hip girths ratio (161). No significant evidence of linkage was found with markers of the LEPR, NPYY1, GLP1, GLP1R, and UCP1 genes (161).

Two studies performed in the Québec Family Study data reported significant linkages between body fat variables and polymorphims in the LEPR gene (108) and between respiratory quotient and the ATP1A2 gene on 1q22-q25 (116). In a study of 105 Finnish obese sib pairs, markers covering a 14-cM region around the MC4R gene were found to be linked with obesity (162). Finally, evidence of linkage was reported between abdominal visceral fat measured by computed tomography and the IGF1 gene on chromosome 12q22-q23 (106).

Conclusions

  1. Top of page
  2. Abstract
  3. Introduction
  4. Single Gene Mutations
  5. Mendelian Disorders
  6. Quantitative Trait Loci (QTL) from Crossbreeding Experiments
  7. Association Studies
  8. Linkage Studies
  9. Conclusions
  10. Acknowledgments
  11. References

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 obesity gene map depicted in Figure 1 reveals that putative loci affecting obesity-related phenotypes are found on all but chromosome Y of the human chromosomes, with chromosomes 14 and 21 showing only one putative locus. Results from genomic scans reveal several new human QTLs related to body fat, energy expenditure, and respiratory quotient. The number of animal QTLs increased from 67 to 98. Results from association studies with candidate genes indicate that the number of candidate genes associated with obesity-related phenotypes has increased from 26 to 40 since the 1998 update.

The number of genes and other markers associated or linked with human obesity phenotypes continues to expand and reaches now well over 200. 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.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Single Gene Mutations
  5. Mendelian Disorders
  6. Quantitative Trait Loci (QTL) from Crossbreeding Experiments
  7. Association Studies
  8. Linkage Studies
  9. Conclusions
  10. Acknowledgments
  11. References

The research of the authors on the genetics of obesity is funded by the Medical Research Council of Canada (PG-11811, MT-13960, and GR-15187). C. Bouchard is supported by the George A. Bray Chair in Nutrition. Thanks are expressed to Diane Drolet, MSc, for her dedicated contribution to the compendium and the development of the manuscript, and to Sophie Gagnon for her help in gathering references. The list of genes and markers currently in the map as well as the pictorial representation of the map is also available on the Web site of the Donald B. Brown Research Chair on Obesity at the following address: http:www.obesity.chair.ulaval.cagenes.html.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Single Gene Mutations
  5. Mendelian Disorders
  6. Quantitative Trait Loci (QTL) from Crossbreeding Experiments
  7. Association Studies
  8. Linkage Studies
  9. Conclusions
  10. Acknowledgments
  11. References
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