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. 2009 Dec 22;10:143. doi: 10.1186/1471-2350-10-143

A tagging SNP in INSIG2 is associated with obesity-related phenotypes among Samoans

Ranjan Deka 1,✉, Ling Xu 1, Prodipto Pal 1, Palanitina T Toelupe 2, Tuiasina S Laumoli 3, Huifeng Xi 1, Ge Zhang 4, Daniel E Weeks 5, Stephen T McGarvey 6
PMCID: PMC2804583  PMID: 20028541

Abstract

Background

A genome wide association study found significant association of a sequence variant, rs7566605, in the insulin-induced gene 2 (INSIG2) with obesity. However, the association remained inconclusive in follow-up studies. We tested for association of four tagging SNPs (tagSNPs) including this variant with body mass index (BMI) and abdominal circumference (ABDCIR) in the Samoans of the Western Pacific, a population with high levels of obesity.

Methods

We studied 907 adult Samoan participants from a longitudinal study of adiposity and cardiovascular disease risk in two polities, American Samoa and Samoa. Four tagSNPs were identified from the Chinese HapMap database based on pairwise r2 of ≥0.8 and minor allele frequency of ≥0.05. Genotyping was performed using the TaqMan assay. Tests of association with BMI and ABDCIR were performed under the additive model.

Results

We did not find association of rs7566605 with either BMI or ABDCIR in any group of the Samoans. However, the most distally located tagSNPs in Intron 3 of the gene, rs9308762, showed significant association with both BMI (p-value 0.024) and ABDCIR (p-value 0.009) in the combined sample and with BMI (p-value 0.038) in the sample from Samoa.

Conclusion

Although rs7566605 was not significantly associated with obesity in our study population, we can not rule out the involvement of INSIG2 in obesity related traits as we found significant association of another tagSNP in INSIG2 with both BMI and ABDCIR. This study suggests the importance of comprehensive assessment of sequence variants within a gene in association studies.

Background

Using genome-wide association analysis, Herbert et al. [1] reported a common variant, rs7566605, in the 5' region of the INSIG2 gene associated with obesity in the Framingham Heart Study population samples and also replicated this finding in four independent cohorts of European and African American ancestries. However, the association of this variant remains inconclusive with confirmation or lack thereof in several follow-up studies conducted in populations of diverse ethnicities [2-12]. Analysis of a single variant could be perceived as a limitation in assessing genetic association of a putative locus. To guard against this potential limitation we conducted a comprehensive association analysis of common tagging SNPs in the INSIG2 gene among adult Samoans, Polynesians of the Western Pacific, residing in Samoa and American Samoa.

Methods

Our study sample derives from a longitudinal study of adiposity and cardiovascular disease risk factors performed in American Samoa and Samoa from 1990 to 1995. Compared to most worldwide populations, the levels of overweight and obesity are remarkably high among Samoans [13-15]. Our sample of Samoans was collected in two territories, the independent nation of Samoa and the U.S. territory of American Samoa. Although there is substantial economic disparity between the two polities, Samoans from both territories form a single socio-cultural unit with frequent exchange of mates and genetically they represent a single homogenous population without any evidence for significant population substructure as supported by our prior genetic analyses [16-18]. Participants were between 18 and 84 years of age with all four grandparents of Samoan ancestry. Detailed descriptions of the sampling and recruitment are reported previously [19,20]. Anthropometric measurements at the baseline in 1990 and 1991 were obtained following standard protocols. For this study, two phenotypes of interest, used as surrogates for obesity, were BMI ((weight in kg)/(height in m2)) and ABDCIR (in cm). This study sample was restricted to those 907 participants with a fasting glucose level of ≤110 mg/dL in order to reduce the confounding of hyperglycemia and type 2 diabetes on the obesity traits. Two of the 907 subjects were on anti-diabetic medication. The mean age was 38.5 years (38.1 in Samoa and 39.0 in American Samoa). The mean BMI and ABDCIR were higher in American Samoa compared to Samoa (Table 1). Study protocols were approved by the Institutional Review Boards of the Miriam Hospital and Brown University, Providence, RI, and officials of the Samoa Ministry of Health and the Department of Health in American Samoa. Written informed consent was obtained from all participants.

Table 1.

Summary of participants, age and basic statistics (Mean ± SD) of the two phenotypes

Age (yrs) BMI (kg/height in m2)
Range: 17.9 - 62.3		 ABDCIR (cm)
Range: 65.6 - 164.1
Combined sample (N = 907) 38.5 ± 9.3 32.0 ± 6.1 100.4 ± 15.1
Male (N = 404) 38.7 ± 9.3 30.9 ± 5.8 98.0 ± 14.8
Female (N = 503) 38.3 ± 9.3 32.9 ± 6.2 102.4 ± 15.1
Samoa (N = 502) 38.1 ± 8.7 30.0 ± 5.0 95.3 ± 13.1
Male (N = 235) 38.2 ± 8.7 29.1 ± 4.8 92.8 ± 12.5
Female (N = 267) 38.0 ± 8.7 30.9 ± 5.1 97.4 ± 13.3
American Samoa (N = 405) 39.0 ± 10.0 34.4 ± 6.3 106.7 ± 15.0
Male (N = 169) 39.5 ± 10.0 33.3 ± 6.0 105.1 ± 14.9
Female (N = 236) 38.7 ± 9.9 35.2 ± 6.5 107.9 ± 15.0
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Tagging SNPs were selected based on pairwise r2 (≥0.8) among all common SNPs with minor allele frequency (MAF) ≥0.05 using the approach of Carlson et al. [21]. We used the Chinese HapMap database http://www.hapmap.org. Previously we had shown the portability of the tagging SNPs and LD sharing between the Chinese and the Samoans [22]. Four tagSNPs spanning a region of 28 kb in INSIG2 including rs7566605 were identified (Figure 1). Genotyping was performed using the TaqMan assay (Applied Biosystems).

Figure 1.

Figure 1

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Schematic representation of the INSIG2 gene region showing the relative location of the tagging SNPs from 5' end to the 3' end of the gene. Allelic variants at each SNP are shown in parenthesis following the 'rs' numbers of the SNPs; the second allele at each locus represents the minor allele. Linkage disequilibria values, r2 and D', among the SNPs are shown in the boxes.

We used the GenABEL package [23] in R to test for association of the SNPs under the additive model. Empirical p-values maximized over the four SNPs were computed using the emp.qtscore function with 10,000 replicates. Since these empirical p-values adjust for the four SNPs, for each trait, we have carried out 5 tests on various subdivisions of the data. A stringent multiple testing correction for this would be to use the Bonferroni correction, which would require testing at the 0.05/5 = 0.01 level. We adjusted for age in all samples, for location (Samoa and American Samoa) in the combined samples and for sex in the Samoa and American Samoa samples. Of the two obesity measurements, BMI was not normally distributed; therefore, we performed logarithmic transformation of BMI to obtain normality.

Results and Discussion

All of the four SNPs are polymorphic in both locations with minor allele frequencies (MAF) ranging from 17% to 42% (Figure 2). All four SNPs are in HWE (data not shown) with the exception of marginal departures at rs1352083 in the combined male sample (p = 0.053) and rs2161829 in the Samoa female sample (p = 0.051). Since we did not observe significant allele frequency difference between the two polities, we combined the samples and performed tests of association based on the additive model (Table 2). Males and females in this combined sample did not show association of any of the four tagging SNPs either with BMI or ABDCIR. However, when males and females were combined, rs9308762 showed significant association with both BMI (p = 0.024) and ABDCIR (p = 0.009). These results are similar when the test statistic was performed under the recessive model, with both BMI (p = 0.038) and ABDCIR (p = 0.018) showing association with rs9308762. Note that the initial study used the recessive model to fit the association signal [1]. Under additive model, each copy of C allele of rs9308762 was associated with an increase of age and gender adjusted BMI = 0.775 kg/m2 and ABDCIR = 2.08 cm. Then we performed tests of associations separately for samples from Samoa and American Samoa. The results showed a significant association of rs9308762 with BMI in the sample from Samoa, but not in the American Samoa sample.

Figure 2.

Figure 2

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Diagrammatic representation of the distribution of minor allele frequencies with 95% confidence intervals at each SNP in the combined (COM), Samoa (SA), and America Samoa (ASA) samples. Preceding each population designations are the sequential SNP numbers from the 5' to the 3' end, e.g., 1-COM denotes rs7566605 in the combined sample.

Table 2.

Association (empirical p-values) of INSIG2 tagSNPs with BMI and ABDCIR based on additive model (adjusted for age in all samples, for location in the combined samples and for sex in the Samoa and American Samoa samples).

rs7566605 rs1352083 rs2161829 rs9308762
BMI ABDCIR BMI ABDCIR BMI ABDCIR BMI ABDCIR
Combined Male 0.359 0.223 0.690 0.629 0.659 0.217 0.386 0.128
Combined Female 0.988 1.000 0.587 0.263 1.000 0.995 0.063 0.076
Combined Total 0.498 0.563 0.999 0.973 0.898 0.423 0.024 0.009
Samoa 0.411 0.547 0.999 0.999 0.955 0.642 0.038 0.070
Am Samoa 0.998 0.991 1.000 0.959 0.994 0.854 0.618 0.236
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Although we did not find association of rs7566605 with either BMI or ABDCIR, the INSIG2 gene itself is of considerable interest for obesity-related quantitative traits as it is implicated in lipid regulation and synthesis [24,25]. It should be noted that rs7566605 is located 10 kb upstream of INSIG2 and its functional relevance is not yet known. The putative association of rs7566605 could have resulted from linkage disequilibrium (LD) with a functional variant in INSIG2 in the study populations, in which the association was detected. The follow-up replication studies considered only this polymorphism with inconsistent results in populations irrespective of their ethnic affiliations [2-12,26]. Among the Asian populations with whom the Samoans share a more recent ancestry, the association of rs7566605 with obesity has been largely negative [27-30], although one study found significant association with BMI in a population from Uyghur [31]. On account of genetic diversity across populations, the extent of LD among the genetic variants is likely to vary, and this could be one of the reasons for the inconsistent findings. To guard against this potential limitation, we conducted an association analysis of common tagging SNPs in INSIG2 with two obesity-related phenotypes. It should be noted that using both genome-wide microsatellite markers at a spacing of 10 cM and over 7,000 SNPs distributed on chromosome 21, we observed a significantly higher level of LD in the Samoans compared to the European populations [18,22] favoring the identification of a surrogate marker further away from the true variant in the relatively isolated Samoan population. We observed significant association of the most distal SNP rs9308762 with both BMI and ABDCIR in the combined Samoan sample. Although this observation is not in complete agreement with the previous report in which the most significant association was found with rs7566605 [1], our results do not necessarily indicate the existence of different functional variants. A possible explanation is that there is a single functional variant, which is in LD with both rs7566605 and rs9308762. Note that these two SNPs are in elevated LD in the Samoan as well as in the HapMap Chinese population, r2 = 0.37 and 0.45, respectively. It is plausible that the putative causal variant is more strongly associated in Europeans with rs7566605, while in Samoans the stronger association is with rs9308762. Although the observations are somewhat preliminary, these results reaffirm the involvement of INSIG2 in regulation of body weight or pathophysiology of obesity related phenotypes.

Conclusion

Although rs7566605 was not significantly associated with obesity in the Samoan population, this study suggests that sequence variants in INSIG2 likely influence the risk for obesity related traits. Our study reiterates the importance of comprehensive assessment of genetic variants within a gene in association studies.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

STM, DEW and RD collaboratively contributed to the conception and design of the study and drafted the manuscript. PP and HX conducted genotyping of all samples. LX and GZ performed statistical analysis. PTT and TSL provided support and advice for the field work in Samoa and American Samoa, respectively. All authors contributed to the writing of the manuscript, read and approved the final version.

Pre-publication history

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1471-2350/10/143/prepub

Contributor Information

Ranjan Deka, Email: ranjan.deka@uc.edu.

Ling Xu, Email: josephinexu1983@gmail.com.

Prodipto Pal, Email: prod.pal@gmail.com.

Palanitina T Toelupe, Email: ceo@health.gov.ws.

Tuiasina S Laumoli, Email: tuiasinasl@americansamoa.gov.

Huifeng Xi, Email: xihuifeng@gmail.com.

Ge Zhang, Email: zhangge.uc@gmail.com.

Daniel E Weeks, Email: weeks+@pitt.edu.

Stephen T McGarvey, Email: Stephen_McGarvey@brown.edu.

Acknowledgements

This study was supported by NIH grants AG09375, HL52611, DK55406, and DK59642 and from the Dean's fund of the University of Cincinnati College of Medicine. This study was designed and jointly directed by Drs. McGarvey, Weeks and Deka.

References

  1. Herbert A, Gerry NP, McQueen MB, Heid IM, Pfeufer A, Illig T, Wichmann H-E, Meitinger T, Hunter D, Hu FB, Colditz G, Hinney A, Hebebrand J, Koberwitz K, Zhu X, Cooper R, Ardlie K, Lyon H, Hirschhorn JN, Laird NM, Lange C, Christman MF. A common genetic variant is associated with adult and childhood obesity. Science. 2006;312:279–283. doi: 10.1126/science.1124779. [DOI] [PubMed] [Google Scholar]
  2. Hall DH, Rahman T, Avery PJ, Keavney B. INSIG-2 promoter polymorphism and obesity related phenotypes: association study in 1428 members of 248 families. BMC Med Genet. 2006;7:83. doi: 10.1186/1471-2350-7-83. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Dina C, Meyre D, Samson C, Tichet J, Marre M, Jouret B, Charles MA, Balkau B, Froguel P. Comment on "A common genetic variant is associated with adult and childhood obesity". Science. 2007;315:187. doi: 10.1126/science.1129402. [DOI] [PubMed] [Google Scholar]
  4. Loos RJ, Barroso I, O'rahilly S, Wareham NJ. Comment on "A common genetic variant is associated with adult and childhood obesity". Science. 2007;315:187. doi: 10.1126/science.1130012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Lyon HN, Emilsson V, Hinney A, Heid IM, Lasky-Su J, Zhu X, Thorleifsson G, Gunnarsdottir S, Walters GB, Thorsteinsdottir U, Kong A, Gulcher J, Nguyen TT, Scherag A, Pfeufer A, Meitinger T, Bronner G, Rief W, Soto-Quiros ME, Avila L, Klanderman B, Raby BA, Silverman EK, Weiss ST, Laird N, Ding X, Groop L, Tuomi T, Isomaa B, Bengtsson K, Butler JL, Cooper RS, Fox CS, O'Donnell CJ, Vollmert C, Celedon JC, Wichmann HE, Hebebrand J, Stefansson K, Lange C, Hirschhorn JN. The association of a SNP upstream of INSIG2 with body mass index is reproduced in several but not all cohorts. PLoS Genet. 2007;3:e61. doi: 10.1371/journal.pgen.0030061. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Rosskopf D, Bornhorst A, Rimmbach C, Schwahn C, Kayser A, Kruger A, Tessmann G, Geissler I, Kroemer HK, Volzke H. Comment on "A common genetic variant is associated with adult and childhood obesity". Science. 2007;315:187. doi: 10.1126/science.1130571. [DOI] [PubMed] [Google Scholar]
  7. Smith AJ, Cooper JA, Li LK, Humphries SE. INSIG2 gene polymorphism is not associated with obesity in Caucasian, Afro-Caribbean and Indian subjects. Int J Obesity. 2007;31:1753–1755. doi: 10.1038/sj.ijo.0803645. [DOI] [PubMed] [Google Scholar]
  8. Andreasen CH, Mogensen MS, Borch-Johnsen K, Sandbaek A, Lauritzen T, Sørensen TI, Hansen L, Almind K, Jørgensen T, Pedersen O, Hansen T. Non-replication of genome-wide based associations between common variants in INSIG2 and PFKP and obesity in studies of 18,014 Danes. PLoS ONE. 2008;3:e2872. doi: 10.1371/journal.pone.0002872. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Boes E, Kollertis B, Heid TM, Hunt SC, Pichler M, Paulweber B, Coassin S, Adams TD, Hopkins PN, Lingenhel A, Wagner SA, Kronenberg F. INSIG2 polymorphism is neither associated with BMI nor with phenotypes of lipoprotein metabolism. Obesity. 2008;16:827–33. doi: 10.1038/oby.2007.132. [DOI] [PubMed] [Google Scholar]
  10. Yang L, Wu Y, Li H, Yu Z, Li X, Liu Y, Lin X, Chen Y. Potential association of INSIG2 rs7566605 polymorphism with body weight in a Chinese population. Eur J Jum Genet. 2008;16:759–761. doi: 10.1038/ejhg.2008.8. [DOI] [PubMed] [Google Scholar]
  11. Vimaleswaran KS, Franks PW, Brage S, Sardinha LB, Andersen LB, Wareham NJ, Ekelung U, Loos RJ. Absence of association between the INSIG2 gene polymorphism (rs7566605) and obesity in the European Youth Heart Study (EYHS) Obesity. 2009. in press PMID: 19197262. [DOI] [PubMed]
  12. Wiedmann S, Neureuther K, Stark K, Reinhard W, Kallmunzer B, Baessler A, Fischer M, Linsel-Nitschke P, Erdmann J, Schunkert H, Hangstenberg C. Lack of association between a common polymorphism near the INSIG2 gene and BMI, myocardial infarction, and cardiovascular risk factors. Obesity. 2009. in press PMID: 19197259. [DOI] [PubMed]
  13. McGarvey ST. Obesity in Samoans and a perspective on etiology in Polynesians. Am J Clin Nutr. 1991;53:1586–1594. doi: 10.1093/ajcn/53.6.1586S. [DOI] [PubMed] [Google Scholar]
  14. Keighley ED, McGarvey ST, Turituri P, Viali S. Farming and Adiposity in Samoan Adults. Am J Hum Biol. 2006;18:112–122. doi: 10.1002/ajhb.20469. [DOI] [PubMed] [Google Scholar]
  15. Åberg K, Dai F, Sun G, Keighley ED, Indugula SR, Roberts ST, Zhang Q, Smelser D, Viali S, Tuitele J, Jin L, Deka R, Weeks DE, McGarvey ST. Susceptibility loci for adiposity phenotypes on 8p, 9p, and 16q in American Samoa and Samoa. Obesity. 2009;17:518–524. doi: 10.1038/oby.2008.558. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. McGarvey ST. Cardiovascular disease (CVD) risk factors in Samoa and American Samoa, 1990-95. Pac Health Dialog. 2001;8:157–162. [PubMed] [Google Scholar]
  17. Deka R, Mc Garvey ST, Ferrell RE, Kamboh MI, Yu LM, Aston CE, Jin L, Chakraborty R. Genetic characterization of American and Western Samoans. Hum Biol. 1994;66:805–22. [PubMed] [Google Scholar]
  18. Tsai H-J, Sun G, Smelser D, Viali S, Tufa J, Jin L, Weeks DE, McGarvey ST, Deka R. Distribution of genome-wide linkage disequilibrium based on microsatellite loci in the Samoan population. Hum Genomics. 2004;1:327–334. doi: 10.1186/1479-7364-1-5-327. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. McGarvey ST, Levinson PD, Bausserman L, Galanis DJ, Hornick C. Population change in adult obesity and blood lipids in American Samoa from 1976-78 to 1990. Am J Hum Biol. 1993;5:17–30. doi: 10.1002/ajhb.1310050106. [DOI] [PubMed] [Google Scholar]
  20. Galanis DJ, McGarvey ST, Quested C, Sio B, Afele-Fa'amuli S. Dietary intake among modernizing Samoans: Implications for risk of cardiovascular disease. J Am Dietetics Assoc. 1999;99:184–190. doi: 10.1016/S0002-8223(99)00044-9. [DOI] [PubMed] [Google Scholar]
  21. Carlson CS, Eberle MA, Rieder MJ, Yi Q, Kruglyak L, Nickerson DA. Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. Am J Hum Genet. 2004;74:106–120. doi: 10.1086/381000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Deka R, Huang W, He Y, Wang H, Wang Y, Li H, Weeks DE, McGarvey ST, Jin L. Portability of the HapMap: linkage disequilibrium sharing between the continental populations and the Samoans of Polynesia. 55th Am Soc Hum Genet Meeting. 2005;A222 [Google Scholar]
  23. Aulchenko YS, Ripke S, Isaacs A, van Duijn CM. GenABEL: an R library for genome-wide association analysis. Bioinformatics. 2007;23:1294–1296. doi: 10.1093/bioinformatics/btm108. [DOI] [PubMed] [Google Scholar]
  24. Yabe D, Komuro R, Liang G, Goldstein JL, Brown MS. Liver-specific mRNA for Insig-2 down-regulated by insulin: implications for fatty acid synthesis. Proc Natl Acad Sci USA. 2003;100:3155–3160. doi: 10.1073/pnas.0130116100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Gong Y, Lee JN, Brown MS, Goldstein JL, Ye J. Juxtamembranous aspartic acid in Insig-1 and Insig-2 is required for cholesterol homeostasis. Proc Natl Acad Sci USA. 2006;103:6154–6159. doi: 10.1073/pnas.0601923103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Bressler J, Fornage M, Hanis CL, Kao WH, Lewis CE, McPherson R, Dent R, Mosely TH, Pennacchio LA, Boerwinkle E. The INSIG2 rs7566605 genetic variant does not play a major role in obesity in a sample of 24,722 individuals from four cohorts. BMC Med Genet. 2009;10:56. doi: 10.1186/1471-2350-10-56. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Kuzuya M, Ando F, Iguchi A, Shimokata H. No association between rs7566605 variant and being overweight in Japanese. Obesity. 2007;15:2531–2534. doi: 10.1038/oby.2007.301. [DOI] [PubMed] [Google Scholar]
  28. Yang L, Wu Y, Li H, Yu Z, Li X, Chen Y. Potential association of INSIG2 rs7566605 polymorphism with body weight in a Chinese subpopulation. Eur J Hum Genet. 2008;16:759–761. doi: 10.1038/ejhg.2008.8. [DOI] [PubMed] [Google Scholar]
  29. Oki K, Yamane K, Kamei N, Asao T, Awaya T, Kohno N. The single nucleotide polymorphism upstream of Insulin-Induced gene 2 (INSIG2) is associated with the prevalence of hypercholesterolaemia, but not with obesity, in Japanese American women. Br J Nutr. 2008;23:1–6. doi: 10.1017/S0007114508006557. [DOI] [PubMed] [Google Scholar]
  30. Tabara Y, Kawamoto R, Osawa H, Nakura J, Makino H, Miki T, Kohara K. No association between INSIG2 gene rs7566605 polymorphism and being overweight in Japanese population. Obesity. 2008;16:211–215. doi: 10.1038/oby.2007.25. [DOI] [PubMed] [Google Scholar]
  31. Zhang J, Lin R, Wang F, Lu M, Lin RY, Wang SZ, Wen H, Jin L, Wang XF. A common polymorphism is associated with body mass index in Uyghur population. Diabetes Res Clin Pract. 2008;81:e11–13. doi: 10.1016/j.diabres.2008.03.022. [DOI] [PubMed] [Google Scholar]

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