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A thrifty variant in CREBRF strongly influences body mass index in Samoans

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Minster, Ryan L, Hawley, Nicola L, Su, Chi-Ting, Sun, Guangyun, Kershaw, Erin E, Cheng, Hong, Buhule, Olive D, Lin, Jerome, Reupena, Muagututi'a Sefuiva, Viali, Satupa'itea, Tuitele, John, Naseri, Take, Urban, Zsolt, Deka, Ranjan, Weeks, Daniel E, McGarvey, Stephen T·2016·Nature Genetics
DOI 10.1038/ng.3620
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Abstract

Samoans are a unique founder population with a high prevalence of obesity, making them well suited for identifying new genetic contributors to obesity. We conducted a genome-wide association study (GWAS) in 3,072 Samoans, discovered a variant, rs12513649, strongly associated with body mass index (BMI) (P = 5.3 × 10−14), and replicated the association in 2,102 additional Samoans (P = 1.2 × 10−9). Targeted sequencing identified a strongly associated missense variant, rs373863828 (p.Arg457Gln), in CREBRF (meta P = 1.4 × 10−20). Although this variant is extremely rare in other populations, it is common in Samoans (frequency of 0.259), with an effect size much larger than that of any other known common BMI risk variant (1.36–1.45 kg/m2 per copy of the risk-associated allele). In comparison to wild-type CREBRF, the Arg457Gln variant when overexpressed selectively decreased energy use and increased fat storage in an adipocyte cell model. These data, in combination with evidence of positive selection of the allele encoding p.Arg457Gln, support a 'thrifty' variant hypothesis as a factor in human obesity.

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Research works printed but not linked: 52

  1. Åberg, K. et al. Susceptibility loci for adiposity phenotypes on 8p, 9p, and 16q in American Samoa and Samoa. Obesity (Silver Spring) 17, 518–524 (2009). · DOI
  2. McGarvey, S.T. Obesity in Samoans and a perspective on its etiology in Polynesians. Am. J. Clin. Nutr. 53 (Suppl. 6), 1586S–1594S (1991). · DOI
  3. Hawley, N.L. et al. Prevalence of adiposity and associated cardiometabolic risk factors in the Samoan genome-wide association study. Am. J. Hum. Biol. 26, 491–501 (2014). · DOI
  4. Tishkoff, S. Strength in small numbers. Science 349, 1282–1283 (2015). · doi:10.1126/science.aad0584
  5. McGarvey, S.T., Bindon, J.R., Crews, D.E. & Schendel, D.E. in Human Population Biology: A Transdisciplinary Science (eds. Little, M.A. & Haas, J.D.) 263–279 (Academic Press, 1989).
  6. McGarvey, S.T. The thrifty gene concept and adiposity studies in biological anthropology. J. Polyn. Soc. 103, 29–42 (1994).
  7. Zimmet, P., Dowse, G., Finch, C., Serjeantson, S. & King, H. The epidemiology and natural history of NIDDM—lessons from the South Pacific. Diabetes Metab. Rev. 6, 91–124 (1990). · DOI · Paper page
  8. Kirch, P.V. & Rallu, J.-L. in The Growth and Collapse of Pacific Island Societies (eds. Kirch, P.V. & Rallu, J.-L.) 1–14 (University of Hawaii Press, 2007). · DOI
  9. Friedlaender, J.S. et al. The genetic structure of Pacific Islanders. PLoS Genet. 4, e19 (2008). · DOI · Paper page
  10. Tsai, H.-J. et al. Distribution of genome-wide linkage disequilibrium based on microsatellite loci in the Samoan population. Hum. Genomics 1, 327–334 (2004). · DOI
  11. Green, R.C. in The Growth and Collapse of Pacific Island Societies (eds. Kirch, P.V. & Rallu, J.-L.) 203–231 (University of Hawaii Press, 2007).
  12. Kichaev, G. et al. Integrating functional data to prioritize causal variants in statistical fine-mapping studies. PLoS Genet. 10, e1004722 (2014). · DOI · Paper page
  13. Loos, R.J. & Yeo, G.S. The bigger picture of FTO: the first GWAS-identified obesity gene. Nat. Rev. Endocrinol. 10, 51–61 (2014). · DOI · Paper page
  14. Speliotes, E.K. et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42, 937–948 (2010). · DOI · Paper page
  15. Eicher, J.D. et al. GRASP v2.0: an update on the Genome-Wide Repository of Associations between SNPs and phenotypes. Nucleic Acids Res. 43, D799–D804 (2015). · DOI
  16. Leslie, R., O'Donnell, C.J. & Johnson, A.D. GRASP: analysis of genotype–phenotype results from 1390 genome-wide association studies and corresponding open access database. Bioinformatics 30, i185–i194 (2014). · DOI · Paper page
  17. Pearce, L.R. et al. KSR2 mutations are associated with obesity, insulin resistance, and impaired cellular fuel oxidation. Cell 155, 765–777 (2013). · DOI · Paper page
  18. Vankoningsloo, S. et al. CREB activation induced by mitochondrial dysfunction triggers triglyceride accumulation in 3T3-L1 preadipocytes. J. Cell Sci. 119, 1266–1282 (2006). · DOI
  19. Reusch, J.E., Colton, L.A. & Klemm, D.J. CREB activation induces adipogenesis in 3T3-L1 cells. Mol. Cell. Biol. 20, 1008–1020 (2000). · DOI · Paper page
  20. Ma, X. et al. CREBL2, interacting with CREB, induces adipogenesis in 3T3-L1 adipocytes. Biochem. J. 439, 27–38 (2011). · DOI
  21. Kim, T.H. et al. Identification of Creb3l4 as an essential negative regulator of adipogenesis. Cell Death Dis. 5, e1527 (2014). · DOI
  22. Keuper, M. et al. Spare mitochondrial respiratory capacity permits human adipocytes to maintain ATP homeostasis under hypoglycemic conditions. FASEB J. 28, 761–770 (2014). · DOI
  23. Tiebe, M. et al. REPTOR and REPTOR-BP regulate organismal metabolism and transcription downstream of TORC1. Dev. Cell 33, 272–284 (2015). · DOI
  24. Stocker, H. Stress relief downstream of TOR. Dev. Cell 33, 245–246 (2015). · DOI
  25. Chen, R., Mallelwar, R., Thosar, A., Venkatasubrahmanyam, S. & Butte, A.J. GeneChaser: identifying all biological and clinical conditions in which genes of interest are differentially expressed. BMC Bioinformatics 9, 548 (2008). · DOI
  26. Dengjel, J. et al. Autophagy promotes MHC class II presentation of peptides from intracellular source proteins. Proc. Natl. Acad. Sci. USA 102, 7922–7927 (2005). · DOI · Paper page
  27. Martyn, A.C. et al. Luman/CREB3 recruitment factor regulates glucocorticoid receptor activity and is essential for prolactin-mediated maternal instinct. Mol. Cell. Biol. 32, 5140–5150 (2012). · DOI
  28. Neel, J.V. Diabetes mellitus: a “thrifty” genotype rendered detrimental by “progress”? Am. J. Hum. Genet. 14, 353–362 (1962).
  29. Kampstra, P. Beanplot: a boxplot alternative for visual comparison of distributions. J. Stat. Softw. 28, 1–9 (2008). · DOI · Paper page
  30. Gauderman, W.J. Sample size requirements for association studies of gene–gene interaction. Am. J. Epidemiol. 155, 478–484 (2002). · DOI · Paper page
  31. Gauderman, W.J. Sample size requirements for matched case–control studies of gene–environment interaction. Stat. Med. 21, 35–50 (2002). · DOI · Paper page
  32. McGarvey, S.T., Levinson, P.D., Bausserman, L., Galanis, D.J. & Hornick, C.A. Population-change in adult obesity and blood-lipids in American-Samoa from 1976–1978 to 1990. Am. J. Hum. Biol. 5, 17–30 (1993). · doi:10.1002/ajhb.1310050106
  33. Keighley, E.D., McGarvey, S.T., Turituri, P. & Viali, S. Farming and adiposity in Samoan adults. Am. J. Hum. Biol. 18, 112–122 (2006). · DOI
  34. Swinburn, B.A., Ley, S.J., Carmichael, H.E. & Plank, L.D. Body size and composition in Polynesians. Int. J. Obes. Relat. Metab. Disord. 23, 1178–1183 (1999). · DOI · Paper page
  35. Cole, T.J., Bellizzi, M.C., Flegal, K.M. & Dietz, W.H. Establishing a standard definition for child overweight and obesity worldwide: international survey. Br. Med. J. 320, 1240–1243 (2000). · DOI · Paper page
  36. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 35 (Suppl. 1), S64–S71 (2012). · DOI · Paper page
  37. Laurie, C.C. et al. Quality control and quality assurance in genotypic data for genome-wide association studies. Genet. Epidemiol. 34, 591–602 (2010). · DOI · Paper page
  38. Heath, S.C. et al. Investigation of the fine structure of European populations with applications to disease association studies. Eur. J. Hum. Genet. 16, 1413–1429 (2008). · DOI · Paper page
  39. Chen, W.M. & Abecasis, G.R. Family-based association tests for genomewide association scans. Am. J. Hum. Genet. 81, 913–926 (2007). · DOI · Paper page
  40. Delaneau, O., Howie, B., Cox, A.J., Zagury, J.F. & Marchini, J. Haplotype estimation using sequencing reads. Am. J. Hum. Genet. 93, 687–696 (2013). · DOI · Paper page
  41. Delaneau, O., Zagury, J.F. & Marchini, J. Improved whole-chromosome phasing for disease and population genetic studies. Nat. Methods 10, 5–6 (2013). · DOI · Paper page
  42. Delaneau, O. & Marchini, J. 1000 Genomes Project Consortium; 1000 Genomes Project Consortium. Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel. Nat. Commun. 5, 3934 (2014). · DOI · Paper page
  43. Marchini, J. & Howie, B. Genotype imputation for genome-wide association studies. Nat. Rev. Genet. 11, 499–511 (2010). · DOI · Paper page
  44. Wang, X. et al. Evaluation of transethnic fine mapping with population-specific and cosmopolitan imputation reference panels in diverse Asian populations. Eur. J. Hum. Genet. 24, 592–599 (2016). · DOI
  45. Aulchenko, Y.S., Struchalin, M.V. & van Duijn, C.M. ProbABEL package for genome-wide association analysis of imputed data. BMC Bioinformatics 11, 134 (2010). · DOI · Paper page
  46. Bradford, M.M. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72, 248–254 (1976). · DOI · Paper page
  47. Staples, J., Nickerson, D.A. & Below, J.E. Utilizing graph theory to select the largest set of unrelated individuals for genetic analysis. Genet. Epidemiol. 37, 136–141 (2013). · DOI
  48. Staples, J. et al. PRIMUS: rapid reconstruction of pedigrees from genome-wide estimates of identity by descent. Am. J. Hum. Genet. 95, 553–564 (2014). · DOI
  49. Cadzow, M. et al. A bioinformatics workflow for detecting signatures of selection in genomic data. Front. Genet. 5, 293 (2014). · DOI
  50. Szpiech, Z.A. & Hernandez, R.D. selscan: an efficient multithreaded program to perform EHH-based scans for positive selection. Mol. Biol. Evol. 31, 2824–2827 (2014). · DOI · Paper page
  51. Voight, B.F., Kudaravalli, S., Wen, X. & Pritchard, J.K. A map of recent positive selection in the human genome. PLoS Biol. 4, e72 (2006). · DOI · Paper page
  52. Ferrer-Admetlla, A., Liang, M., Korneliussen, T. & Nielsen, R. On detecting incomplete soft or hard selective sweeps using haplotype structure. Mol. Biol. Evol. 31, 1275–1291 (2014). · DOI · Paper page

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Metadata

Authors
Minster, R. L., Hawley, N. L., Su, C.-T., Sun, G., Kershaw, E. E., Cheng, H., Buhule, O. D., Lin, J., Reupena, M. S., Viali, S., Tuitele, J., Naseri, T., Urban, Z., Deka, R., Weeks, D. E., & McGarvey, S. T.
Venue
Nature Genetics
Publisher
Springer Science and Business Media LLC
Published
2016-07-25
Volume
48
Issue
9
Pages
1049-1054
ISSN
  • 1061-4036 (ISSN-L)
  • 1546-1718
DOI
10.1038/ng.3620
OpenAlex
W2488609201
Cited by
262
References
15
FWCI
19.32
Type
journal article
Language
en
Open access
green
Licence
www.springer.com/tdm (tdm)

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CoChat. (2026). Citation check: A thrifty variant in CREBRF strongly influences body mass index in Samoans. https://app.cochat.ai/papers/10.1038/ng.3620
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Minster, R. L., Hawley, N. L., Su, C.-T., Sun, G., Kershaw, E. E., Cheng, H., Buhule, O. D., Lin, J., Reupena, M. S., Viali, S., Tuitele, J., Naseri, T., Urban, Z., Deka, R., Weeks, D. E., & McGarvey, S. T. (2016). A thrifty variant in CREBRF strongly influences body mass index in Samoans. Nature Genetics. https://doi.org/10.1038/ng.3620

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