This Article Abstract Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Hegele, R. A. Articles by Connelly, P. W. Search for Related Content PubMed PubMed Citation Articles by Hegele, R. A. Articles by Connelly, P. W.

(Circulation. 1995;92:1089-1093.)
© 1995 American Heart Association, Inc.

Articles

Genetic Variation on Chromosome 1 Associated With Variation in Body Fat Distribution in Men

Robert A. Hegele, MD; J. Howard Brunt, PhD; Philip W. Connelly, PhD

From the Departments of Medicine (R.A.H., P.W.C.), Clinical Biochemistry (R.A.H., P.W.C.), and Biochemistry (P.W.C.), St Michael's Hospital, University of Toronto, Ontario; and School of Nursing (J.H.B.), University of Victoria, British Columbia, Canada.

Correspondence to Robert A. Hegele, MD, DNA Research Laboratory, St Michael's Hospital, 30 Bond St, Toronto, Ontario, Canada M5B 1W8.

	Abstract

Top Abstract Introduction Methods Results Discussion References

 
Background Interindividual variation in fat deposition in swine is determined by loci on porcine chromosome 4, which are contained in a region that is syntenic with part of the long arm of human chromosome 1. We hypothesized that genomic variation of chromosome 1q would be associated with variation in the ratio of waist-to-hip circumference in male North American Hutterites, a genetic isolate characterized by significant relatedness and sharing of environmental factors.

Methods and Results In 316 male Hutterites, we tested for phenotype-genotype association of two DNA polymorphisms on chromosome 1q and the ratio of waist-to-hip circumference. We included control loci on 10 other chromosomes in the multivariate model. We observed that DNA variation on chromosome 1q was significantly associated with variation in the ratio of waist-to-hip circumference in men (P=.0029).

Conclusions The association of DNA variation chromosome 1q with the ratio of waist-to-hip circumference in male Hutterites suggests that there are important structural elements in this genomic region that have a functional impact on body fat distribution.

Key Words: genetics • obesity

	Introduction

Top Abstract Introduction Methods Results Discussion References

 
Human obesity is a complex quantitative trait that is considered to be influenced by both genetic and environmental factors.^{1 2 3 4 5 6 7 8 9 10 11 12} Analysis of the genetic determinants of variation in ponderal indexes must account for both the gene products that contribute to pathogenesis and their interactions with hormonal and environmental factors.^{10 11 12} Through study of genetically isolated populations, such as the Hutterite Brethren of North America,¹³ we can identify genetic components of complex quantitative traits.^{14 15 16} We believed that the Hutterites could be studied to identify genetic determinants of the ratio of waist-to-hip circumference (WHR), an index of visceral fat deposition that is associated with increased atherosclerosis risk.⁶ We have taken advantage of variation in human genomic regions that are syntenic with variation in fat deposition in animal models. Two of the single gene mutations causing obesity in mice—db on murine chromosome 4 and fat on murine chromosome 8—were linked to type I anchor loci corresponding to loci on human chromosome 1.¹⁷ Furthermore, variation in abdominal and back fat distribution in pigs was determined by loci on porcine chromosome 4 that were close to three type I anchor loci, ie, ATP1A1, ATP1B1, and GBA, all of which correspond to loci on human chromosome 1q13-q21.¹⁸ We previously genotyped 12 loci on 11 chromosomes in the Hutterites, including the AGT locus on chromosome 1q42-43.¹⁵ We hypothesized that the Hutterites were sufficiently closely related that the AGT markers would be in linkage disequilibrium with functional variants of the human homologues of the porcine loci determining fat distribution. We tested for association between AGT genotypes and variation in WHR in the Hutterites.

	Methods

Top Abstract Introduction Methods Results Discussion References

 
Study Subjects
The Hutterite Brethren are an Anabaptist sect composed of approximately 30 000 members who live in Western Canada and the adjacent US states. They have an agrarian lifestyle and live on communal farms called colonies.¹³ Contemporary Hutterites are descended from fewer than 100 founders who are considered to be unrelated to each other.^{13 19} The Hutterites have had a high intrinsic growth rate, and their population remains closed to immigration.¹⁹ They are subdivided into three endogamous sects: Dariusleut, Lerherleut, and Schmiedeleut.¹⁹ A high degree of consanguinity relative to the founders has accumulated over approximately 12 generations, with the average inbreeding coefficient of the current generation being 0.05.¹⁹

Hutterite society has a static intergenerational and intragenerational lifestyle.¹³ Colonies are effective surrogates for extended families; women marry between colonies, but men tend to remain within a colony.¹⁹ The prevalence of atherosclerosis risk factors is comparable to that found in other populations.²⁰ Smoking is forbidden, but alcohol is not.²¹ Major meals are taken communally, and the diet is high in animal fat.²¹ Mechanized farming techniques have reduced the amount of aerobic work-related exercise.²⁰

Subjects from 21 colonies of the Alberta Dariusleut and Lerherleut sects took part in the Canadian Heart Health Survey screening for coronary heart disease risk factors.^{22 23} Physical examination included determination of circumferences of waist and hip, body mass index (BMI) defined as ratio of weight to height² (kg/m²), and four separate blood pressure determinations. Plasma samples from 846 Hutterites were obtained with informed consent. Exclusion criteria included an inadequate blood sample available for all biochemical and/or genetic determinations. The study was approved by the ethics review panels of the Universities of Alberta and Toronto.

Genetic Analyses
Sufficient DNA and phenotypic information were obtained for most analyses from 793 Hutterites. Established methods were used to obtain genotypes for AGT codons 174 and 235,¹⁵ APOB codons 3611 and 4154,²⁴ PON codon 192,²⁵ LPL intron 6,²⁶ VLDLR trinucleotide repeat in the 5'-untranslated region,²⁷ APOC3 Sac I site polymorphism in the 3'-untranslated region,²⁸ LRP tetranucleotide repeat in the 5'-untranslated region (5'-tetra),²⁹ clotting factor VII (F7) codon 353 protein polymorphism,³⁰ HL codon 202,³¹ ACE (angiotensin-converting enzyme) insertion-deletion polymorphism,³² LDLR exon 12 HincII site polymorphism,³³ and APOE.³⁴ The chromosomal localization of these genes is included in Table 1.

View this table: [in this window] [in a new window]   Table 1. Markers Used for Genotyping Hutterites

Statistical Analysis
SAS (Version 6) was used for all statistical comparisons.³⁵ Each quantitative variable was transformed and subjected to analysis of normality. Because indexes of obesity differ between men and women, the sexes were analyzed separately. Logarithmically transformed WHR, BMI, and systolic blood pressure had distributions that did not differ from normal (data not shown). The transformed variables were used for statistical analyses, but the nontransformed mean and standard deviation values are presented in Table 2.

View this table: [in this window] [in a new window]   Table 2. ANOVA in Male Hutterites

ANOVA was performed using the General Linear Models procedure to determine the sources of variation of WHR. F tests were computed from the type III sums of squares³⁵ ; this form of the sums of squares applies to unbalanced study designs and reports the effect of an independent variable after adjustment for all other variables included in the model. The analysis was performed separately for men and women. The dependent variable was the natural logarithm of WHR. The independent variables were age, colony of origin (which was included to correct for variation that was related to other shared genetic and environmental factors), logarithm of height (which was included because it was postulated to be related to the dependent variable), and logarithm of systolic blood pressure (which was included because it was previously shown to be associated with variation in AGT, the locus of interest). Also included as independent variables were genotypes of AGT, APOB, PON, LPL, VLDLR, APOC3, LRP, F7, HL, ACE, LDLR, and APOE.

When a significant association was identified within the entire group, baseline traits among individuals classified by genotype were subsequently compared with the use of either a t test for least-squares mean values³⁵ or a nonparametric test for significant differences between groups (Kruskal-Wallis test, ² approximation, NPAR1WAY routine³⁵ ).

	Results

Top Abstract Introduction Methods Results Discussion References

 
Allele and Genotype Frequencies
Allele frequencies for most markers tested were similar to those reported in other white populations (Table 1). However, the minor allele frequencies in the Hutterites compared with other white populations were somewhat increased for the APOB codon 3611, VLDLR, LRP, and F7 genotypes.^{24 27 29 30} The minor allele frequencies in the Hutterites compared with other whites were somewhat decreased for the APOE gene.³⁴ Except for the ACE genotypes, the observed genotype frequencies did not deviate from those predicted by the Hardy-Weinberg law in this sample of Hutterites (data not shown).

Determinants of Variation in WHR
The ANOVA for men is shown in Table 2. At a nominal P=.05, F values in the analysis of the natural logarithm of WHR as the dependent variable and the 14 genetic markers as independent class variables showed that only the genotype of AGT codon 174 contributed significantly to phenotypic variation. Age, colony of origin, and natural logarithm of systolic blood pressure were also found to be significantly associated with variation in the natural logarithm of WHR. The ANOVA for women showed similar associations with age, colony of origin, and systolic blood pressure but no significant association with any genetic variable (data not shown).

Between-Genotype Differences
Least-squares mean values for the significant phenotype-genotype association were compared with the use of a t test (Table 3). The AGT codon 174 genotype system had three genotype classes: T/T (218 subjects), T/M (98 subjects), and M/M (3 subjects). We excluded the 3 M/M subjects, because this group was too small to carry out meaningful pairwise comparisons. Significant pairwise differences between the least-squares mean values of the T/T and T/M classes were found for the natural logarithms of WHR and systolic blood pressure (P=.0011) but not of BMI. Remarkably, the mean systolic blood pressure was higher in T/M subjects than in T/T subjects, but WHR was lower in T/M subjects than in T/T subjects (P=.0066).

View this table: [in this window] [in a new window]   Table 3. Clinical Traits in Male Hutterites Classified by AGT Codon 174 Genotype

	Discussion

Top Abstract Introduction Methods Results Discussion References

 
The principal finding of the study in Hutterites was the identification of a sex-specific association between genetic variation on chromosome 1 and differences in body fat distribution. Specifically, we found a significant association between variation of WHR and variation of AGT codon 174 in men from a genetically isolated population. We found that although the AGT M174 isoform in men was associated with significantly higher systolic blood pressure, it also was associated with a significantly lower WHR. The association of the M174 isoform with higher systolic blood pressure has been previously reported in this and other study samples,^{15 36} but the association with a lower WHR is a new finding.

Because of its association with higher systolic blood pressure, the AGT M174 isoform might have been expected to have been associated with an increased WHR. Systolic blood pressure and indexes of body fat are closely correlated within families,⁸ but blood pressure and body fat might share relatively few genetic determinants.³⁷ In the Hutterites, it is unlikely that the association between the AGT M174 isoform and a lower WHR was due to a direct physiological role of angiotensinogen in determining the distribution of body fat. Instead, we hypothesize that in this sample of male Hutterites, who are closely related and share a restricted gene pool, the AGT M174 isoform acted as a genetic marker for a closely linked gene on the long arm of chromosome 1 that was the actual determinant of the difference in body fat distribution. The loci corresponding on porcine chromosome 4 that determined abdominal and back fatness were syntenic with a region that is more centromeric on chromosome 1q than AGT. Thus, although AGT was a helpful surrogate marker in the Hutterites, the actual genetic determinant of variation of body fat distribution likely lies in close proximity to, but is not identical with, AGT. An approach analogous to quantitative trait locus mapping in inbred animals^{38 39 40} will be required using closely spaced markers in this region to specifically identify the causative gene on human chromosome 1.

The associations of this locus with variations in both blood pressure and WHR were detected only in men. There are several possible explanations for the sex-specificity of these associations, particularly with respect to WHR. For example, WHR differs significantly between the sexes.^{6 7} This could reflect fundamental sex-related differences in physiological determinants of WHR, including differences in the genetic determinants and differences in the gene-environment interactions that produce the measured phenotype. It is also possible that the variation in WHR among women is determined more by environmental factors than is WHR in men. Also, there may be tissue-specific hormonal modulation of the association of the locus with the phenotype, adding another level of complexity to any genotype-phenotype association. The sex-specificity of the association in the Hutterites could also relate to the cultural practice of women marrying between colonies but men remaining within a colony over time, although the mechanistic basis for such a relation is unclear.

We previously showed that there was strong, but not complete, linkage disequilibrium between alleles at AGT codons 174 and 235.¹⁵ This was due mainly to a higher prevalence of subjects homozygous for both 235M and 174T than would have been expected had there been no linkage disequilibrium.¹⁵ The absence of association between alleles of codon 235 and variation in WHR has several possible explanations. For example, alleles at codons 174 and 235 were not independent. Thus, our statistical model would not have detected associations with both if the association was primarily with alleles at one site. Also, linkage disequilibrium between alleles of codon 235 and the actual causative locus might have been dissipated, as has been observed for genes located near telomeres, like AGT.⁴¹ However, the actual basis for the association with WHR observed only for alleles of AGT codon 174 and not for alleles of codon 235 is unclear.

Others have reported associations between obesity and some of the candidate genes that we have tested. For example, variation at APOB was found to be associated with variation in percent body fat⁴² and in BMI.⁴³ Also, variation at LDLR was found to be associated with variation in BMI in hypertensive subjects.⁴⁴ However, variation in these two genes was not found to be associated with either WHR or BMI in the Hutterites. These discrepancies may reflect differences between the study samples related to ethnicity, genetic heterogeneity, environmental differences, ascertainment, or a combination.

Positive phenotype-genotype associations have been found with other candidate genes in unrelated populations. For example, variation at DRD2 (dopamine receptor; chromosome 11q22-23) was found to be associated with obesity⁴⁵ and variation in both weight and height.⁴⁶ Interestingly, one patient with a major deletion affecting chromosome 11p14-p12 had morbid obesity.⁴⁷ Also, variation at INS (insulin; chromosome 11p15.5) was found to be associated with variation in body fat distribution in women.⁴⁸ However, in the Hutterites, variation at APOC3 on chromosome 11q23 was not associated with WHR or BMI in either sex. Although the discrepancies might reflect differences between the study samples related to genetic heterogeneity, it is also possible that APOC3 is not in linkage disequilibrium with a functional locus on chromosome 11 that might actually contribute to variation in obesity phenotypes. More loci will need to be examined as a part of a genomic screen.

Recently, Zhang and colleagues⁴⁹ reported the structure of a mutation of the obesity gene ob on mouse chromosome 6. Homozygosity for this mutation results in the obese phenotype in the mouse. The human homologue has been mapped on chromosome 7q31.¹⁷ This is close to the PON locus on chromosome 7q21-22, which was included in our analysis of the Hutterites. We found no association between variation in either BMI or WHR and PON genotypes in the Hutterites. Although this could be attributed to a loss of linkage disequilibrium between PON and the human homologue of ob in the Hutterites, it might also reflect the heterogeneity of genetic determinants of obesity-related phenotypes and the relative importance of different genes in various populations.

There was a significant phenotype-genotype association between WHR and AGT genotype in the study population, but the absolute difference between genotypic classes was small. This suggests that although genetic variation on chromosome 1q was a statistically significant determinant of WHR, it explains only a small proportion of the total variation in this trait. Thus, environmental factors, such as diet and exercise, and additional genetic loci certainly also contribute to variation in WHR. Analysis of genetic determinants of obesity in the general population will be further obscured by the unique landscape of environmental factors for each person. Genomic screening in related samples could help identify new genes that determine obesity. This might help both to identify individuals who are candidates for intervention and to identify metabolic pathways that may be important targets for new interventional strategies.

	Acknowledgments

 
This work was supported by grants from the Medical Research Council of Canada, the National Health Research and Development Program of Canada, and the Heart and Stroke Foundations of Ontario and Canada. Dr Hegele is a McDonald Scholar of the Heart and Stroke Foundation of Canada. We thank Stanley Chan (APOB codon 3611 genotypes), Kevin Higgins (APOB codon 4154 genotypes), Greg Ip (APOE and LPL genotypes), Ulana Kawun (F7 genotypes), Dennis Lam (LDLR and VLDLR genotypes), Edwin Lee (AGT and PON genotypes), Patricia Ram (AGT and HL genotypes), Stefan Sadikian (LRP and ACE genotypes), and Tammy Znajda (APOC3 genotypes) for their technical assistance. Teresa Lippingwell and Liling Tu archived the phenotypic and genotypic data. Dr Adele Csima, Department of Biostatistics, University of Toronto, provided expert advice regarding our statistical analyses.

Received January 23, 1995; revision received March 3, 1995; accepted March 19, 1995.

	References

Top Abstract Introduction Methods Results Discussion References

 

1. Stunkard AJ, Foch TT, Hrubec Z. A twin study of human obesity. JAMA. 1986;256:51-54. [Abstract]
   
2. Price RA. Genetics of human obesity. Ann Behav Med. 1987;9:9-14.
   
3. Bray GA. Genetic, hypothalamic and endocrine features of clinical and experimental obesity. Prog Brain Res. 1992;93:333-340. [Medline] [Order article via Infotrieve]
   
4. Sorenson TI. Genetic aspects of obesity. Int J Obes Relat Metab Disord. 1992;16:S27-S29.
   
5. Fabsitz RR, Carmelli D, Hewitt JK. Evidence for independent genetic influences for obesity in middle age. Int J Obes Relat Metab Disord. 1992;16:657-666. [Medline] [Order article via Infotrieve]
   
6. Bouchard C, Preusse L. Genetic aspects of obesity. Ann N Y Acad Sci. 1993;699:26-35. [Medline] [Order article via Infotrieve]
   
7. Bouchard C. Genetics of obesity and its prevention. World Rev Nutr Diet. 1993;72:68-77. [Medline] [Order article via Infotrieve]
   
8. Carmelli D, Cardon LR, Fabsitz R. Clustering of hypertension, diabetes and obesity in adult male twins: same genes or same environments? Am J Hum Genet. 1994;55:566-573. [Medline] [Order article via Infotrieve]
   
9. Cardon LR, Carmelli D, Fabsitz RR, Reed T. Genetic and environmental correlations between obesity and body fat distribution in adult male twins. Hum Biol. 1994;66:465-479. [Medline] [Order article via Infotrieve]
   
10. Ferrell RE. Obesity: choosing genetic approaches from a mixed menu. Hum Biol. 1993;65:967-975. [Medline] [Order article via Infotrieve]
    
11. Leibel RL, Bahary N, Friedman JM. Strategies for the molecular genetic analysis of obesity in humans. Crit Rev Food Sci Nutr. 1993;33:351-358. [Medline] [Order article via Infotrieve]
    
12. Bruns TL, Moll PP, Lauer RM. Genetic models of human obesity: family studies. Crit Rev Food Sci Nutr. 1993;33:339-343. [Medline] [Order article via Infotrieve]
    
13. Morgan K, Holmes KT. Population structure of a religious isolate: the Dariusleut Hutterites of Alberta. In Crawford MH, Mielke JH, eds. Current Developments in Anthropological Genetics, Vol 2: Ecology and Population Structure. New York, NY: Plenum; 1983:429-448.
    
14. Hegele RA, Evans AJ, Tu L, Ip G, Brunt JH, Connelly PW. A gene-gender interaction affecting lipoproteins in a genetic isolate. Arterioscler Thromb. 1994;14:671-678. [Abstract/Free Full Text]
    
15. Hegele RA, Brunt JH, Connelly PW. A polymorphism of the angiotensinogen gene associated with variation in blood pressure in a genetic isolate. Circulation. 1994;90:2207-2212. [Abstract/Free Full Text]
    
16. Hegele RA, Brunt JH, Connelly PW. A polymorphism of the paraoxonase gene associated with variation in plasma lipoproteins in a genetic isolate. Arterioscler Thromb Vasc Biol. 1995;15:89-95. [Abstract/Free Full Text]
    
17. O'Brien SJ, Womack JE, Lyons LA, Moore KJ, Jenkins NA, Copeland NG. Anchored reference loci for comparative genome mapping in mammals. Nat Genet. 1993;3:103-112. [Medline] [Order article via Infotrieve]
    
18. Andersson L, Haley CS, Ellegren H, Knott SA, Johansson M, Andersson K, Andersson-Eklund L, Edfors-Lilja I, Fredholm M, Hansson I, Hakansson J, Lundstrom K. Genetic mapping of quantitative trait loci for growth and fatness in pigs. Science. 1994;263:1771-1774. [Abstract/Free Full Text]
    
19. Fujiwara TM, Morgan K, Schwartz RH, Doherty RA, Miller SR, Klinger K, Stanislovits P, Stuart N, Watkins PC. Genealogical analysis of cystic fibrosis families and chromosome 7q RFLP haplotypes in Hutterite brethren. Am J Hum Genet. 1989;44:327-337. [Medline] [Order article via Infotrieve]
    
20. Hostetler JA. History and relevance of the Hutterite population for genetic studies. Am J Med Genet. 1985;45:299-305.
    
21. Brunt JH, Love EJ. Hypertension and its correlates in the Hutterite community of Alberta. Can J Public Health. 1992;83:362-364. [Medline] [Order article via Infotrieve]
    
22. Connelly PW, MacLean DR, Horlick L, O'Connor B, Petrasovits A, Little JA. Plasma lipids and lipoproteins and the prevalence of risk for coronary heart disease in Canadian adults. Can Med Assoc J. 1992;146:1977-1987. [Abstract]
    
23. MacLean DR, Petrasovits A, Nargundkar M, Connelly PW, MacLeod E, Edwards A, Hessel P. Canadian Heart Health Surveys: a profile of cardiovascular risk: survey methods and data analysis. Can Med Assoc J. 1992;146:1971-1976.
    
24. Boerwinkle E, Lee SS, Butler R, Schumaker VN, Chan L. Rapid typing of apolipoprotein B DNA polymorphisms by DNA amplification. Atherosclerosis. 1990;81:225-232. [Medline] [Order article via Infotrieve]
    
25. Humbert R, Adler DA, Disteche CM, Hassett C, Omiecinski CJ, Furlong CE. The molecular basis of the human serum paraoxonase activity polymorphism. Nat Genet. 1993;3:73-76. [Medline] [Order article via Infotrieve]
    
26. Johnson JP, Nishina PM, Naggert JK. PCR assay for a polymorphic site in the LPL gene. Nucl Acids Res. 1991;18:7469.
    
27. Jokinen E, Sakrai J, Yamamoto T, Hobbs HH. CGG triple repeat polymorphism in VLDL receptor (VLDL-R) gene. Hum Mol Genet. 1994;3:521. [Free Full Text]
    
28. Tas S. Strong association of a single nucleotide substitution in the 3'-untranslated region of the apolipoprotein CIII gene with common hypertriglyceridemia in Arabs. Clin Chem. 1989;35:256-259. [Abstract/Free Full Text]
    
29. Zuliani G, Hobbs HH. Tetranucleotide length polymorphism 5' of the 2-macroglobulin receptor (A2MR)/LDL receptor-related protein (LRP) gene. Hum Mol Genet. 1994;3:215. [Free Full Text]
    
30. Humphries SE, Lane A, Green FR, Cooper J, Miller GJ. Factor VII coagulant activity and antigen levels in healthy men are determined by interaction between factor VII genotype and plasma triglyceride concentration. Arterioscler Thromb. 1994;14:193-198. [Abstract/Free Full Text]
    
31. Hegele RA, Tu L, Connelly PW. Human hepatic lipase mutations and polymorphisms. Hum Mutat. 1992;1:320-324. [Medline] [Order article via Infotrieve]
    
32. Tiret L, Rigat B, Visvikis S, Breda C, Corvol P, Cambien F, Soubrier F. Evidence, from combined segregation and linkage analysis, that a variant of the angiotensin I-converting enzyme (ACE) gene controls plasma ACE levels. Am J Hum Genet. 1992;51:197-205. [Medline] [Order article via Infotrieve]
    
33. Leitersdorf E, Hobbs HH. Human LDL receptor HincII polymorphism detected by gene amplification. Nucl Acids Res. 1988;16:7215. [Free Full Text]
    
34. Hixson JE, Vernier DT. Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI. J Lipid Res. 1990;31:545-548. [Abstract]
    
35. SAS Institute Inc. SAS/STAT Guide for Personal Computers, version 6. Cary, NC: SAS Institute Inc; 1987.
    
36. Jeunemaitre X, Soubrier F, Kotelevtsev YV, Lifton RP, Williams CS, Charrer A, Hunt SC, Hopkins PN, Williams RR, Lalouel JM, Corvol P. Molecular basis of human hypertension: role of angiotensinogen. Cell. 1992;71:169-180. [Medline] [Order article via Infotrieve]
    
37. Rice T, Province M, Perusse L, Bouchard C, Rao DC. Cross-trait familial resemblance for body fat and blood pressure: familial correlations in the Quebec family study. Am J Hum Genet. 1994;55:1019-1029. [Medline] [Order article via Infotrieve]
    
38. Warden CH, Fisler JS, Pace MJ, Svenson KL, Lusis AJ. Coincidence of genetic loci for plasma cholesterol levels and obesity in a multifactorial mouse model. J Clin Invest. 1993;92:773-779.
    
39. Nishina PM, Lowe S, Wang J, Paigen B. Characterization of plasma lipids in genetically obese mice: the mutant obese, diabetes, fat, tubby and lethal yellow. Metabolism. 1994;43:549-553. [Medline] [Order article via Infotrieve]
    
40. West DB, Goudey-Lefevre J, York B, Truett G. Dietary obesity linked to genetic loci on chromosomes 9 and 15 in a polygenic mouse model. J Clin Invest. 1994;94:1410-1416.
    
41. Watkins WS, Zenger R, O'Brien E, Nyman D, Eriksson AW, Renlund M, Jorde LB. Linkage disequilibrium patterns vary with chromosomal location: a case study from the von Willebrand factor region. Am J Hum Genet. 1994;55:348-355. [Medline] [Order article via Infotrieve]
    
42. Pouliot M-C, Depres J-P, Dionne FT, Vohl M-C, Moorjani S, Prud'homme D, Bouchard C, Lupien PJ. ApoB-100 gene EcoRI polymorphism: relations to plasma lipoprotein changes associated with abdominal visceral obesity. Arterioscler Thromb. 1994;14:527-533. [Abstract/Free Full Text]
    
43. Saha N, Tay JS, Heng CK, Humphries SE. DNA polymorphisms of the apolipoprotein B gene are associated with obesity and serum lipids in healthy Indians in Singapore. Clin Genet. 1993;22:113-120.
    
44. Zee RY, Griffiths LR, Morris BJ. Marked association of a RFLP for low density lipoprotein receptor gene with obesity in essential hypertensives. Biochem Biophys Res Commun. 1992;189:965-971. [Medline] [Order article via Infotrieve]
    
45. Noble EP, Noble RE, Ritchie T, Syndulko K, Bohlman CM, Noble LA, Zhang Y, Sparkes RS, Grandy DK. D2 dopamine receptor gene and obesity. Int J Eat Disord. 1994;15:205-217. [Medline] [Order article via Infotrieve]
    
46. Comings DE, Flanagan SD, Dietz G, Muhleman D, Knell E, Gysin R. The dopamine D2 receptor (DRD2) as a major gene in obesity and height. Biochem Med Metab Biol. 1993;50:176-185. [Medline] [Order article via Infotrieve]
    
47. Marlin S, Couet D, Lacombe D, Cessans C, Bonneau D. Obesity: a new feature of WAGR (del 11p) syndrome. Clin Dysmorphol. 1994;3:255-257. [Medline] [Order article via Infotrieve]
    
48. Weaver JU, Kopelman PG, Hitman GA. Central obesity and hyperinsulinaemia in women are associated with polymorphism in the 5' flanking region of the human insulin gene. Eur J Clin Invest. 1992;22:265-270. [Medline] [Order article via Infotrieve]
    
49. Zhang Y, Proenca R, Maffel M, Barone M, Leopold L, Friedman JM. Positional cloning of the mouse obese gene and its human homologue. Nature. 1994;372:425-432.[Medline] [Order article via Infotrieve]
    

This article has been cited by other articles:

				S. Engeli, J. Bohnke, K. Gorzelniak, J. Janke, P. Schling, M. Bader, F. C. Luft, and A. M. Sharma Weight Loss and the Renin-Angiotensin-Aldosterone System Hypertension, March 1, 2005; 45(3): 356 - 362. [Abstract] [Full Text] [PDF]

				Y.-J. Lee and J. C.R. Tsai ACE Gene Insertion/Deletion Polymorphism Associated With 1998 World Health Organization Definition of Metabolic Syndrome in Chinese Type 2 Diabetic Patients Diabetes Care, June 1, 2002; 25(6): 1002 - 1008. [Abstract] [Full Text] [PDF]

				S. Engeli, R. Negrel, and A. M. Sharma Physiology and Pathophysiology of the Adipose Tissue Renin-Angiotensin System Hypertension, June 1, 2000; 35(6): 1270 - 1277. [Abstract] [Full Text] [PDF]

				D. A. PRICE, L. E. PORTER, M. GORDON, N. D. L. FISHER, J. M. F. DE'OLIVEIRA, L. M. B. LAFFEL, D. R. PASSAN, G. H. WILLIAMS, and N. K. HOLLENBERG The Paradox of the Low-Renin State in Diabetic Nephropathy J. Am. Soc. Nephrol., November 1, 1999; 10(11): 2382 - 2391. [Abstract] [Full Text]

				L. E. Porter and N. K. Hollenberg Obesity, Salt Intake, and Renal Perfusion in Healthy Humans Hypertension, July 1, 1998; 32(1): 144 - 148. [Abstract] [Full Text] [PDF]

				B. H. Jones, M. K. Standridge, and N. Moustaid Angiotensin II Increases Lipogenesis in 3T3-L1 and Human Adipose Cells Endocrinology, April 1, 1997; 138(4): 1512 - 1519. [Abstract] [Full Text] [PDF]

				D. E.L. Wilcken, X. L. Wang, A. S. Sim, and R. M. McCredie Distribution in Healthy and Coronary Populations of the Methylenetetrahydrofolate Reductase (MTHFR) C677T Mutation Arterioscler. Thromb. Vasc. Biol., July 1, 1996; 16(7): 878 - 882. [Abstract] [Full Text]

This Article Abstract Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Hegele, R. A. Articles by Connelly, P. W. Search for Related Content PubMed PubMed Citation Articles by Hegele, R. A. Articles by Connelly, P. W.