| Literature DB >> 21244673 |
Sean Myles1, Rod A Lea, Jun Ohashi, Geoff K Chambers, Joerg G Weiss, Emilie Hardouin, Johannes Engelken, Donia P Macartney-Coxson, David A Eccles, Izumi Naka, Ryosuke Kimura, Tsukasa Inaoka, Yasuhiro Matsumura, Mark Stoneking.
Abstract
BACKGROUND: the thrifty gene hypothesis posits that, in populations that experienced periods of feast and famine, natural selection favoured individuals carrying thrifty alleles that promote the storage of fat and energy. Polynesians likely experienced long periods of cold stress and starvation during their settlement of the Pacific and today have high rates of obesity and type 2 diabetes (T2DM), possibly due to past positive selection for thrifty alleles. Alternatively, T2DM risk alleles may simply have drifted to high frequency in Polynesians. To identify thrifty alleles in Polynesians, we previously examined evidence of positive selection on T2DM-associated SNPs and identified a T2DM risk allele at unusually high frequency in Polynesians. We suggested that the risk allele of the Gly482Ser variant in the PPARGC1A gene was driven to high frequency in Polynesians by positive selection and therefore possibly represented a thrifty allele in the Pacific.Entities:
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Year: 2011 PMID: 21244673 PMCID: PMC3025936 DOI: 10.1186/1471-2350-12-10
Source DB: PubMed Journal: BMC Med Genet ISSN: 1471-2350 Impact factor: 2.103
Summary statistics of cohorts and results of association between Gly482Ser genotypes and BMI.
| Co-dominant | Dominant | Recessive | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Maori | 110 | 32 | 78 | 48.1 ± 17.7 | 32.1 ± 7.6 | 0.833 | 0.024 ± 1.41 | 0.99 | 0.146 ± 1.60 | 0.93 | -0.907 ± 4.52 | 0.84 |
| Tongans | 184 | 63 | 121 | 46.3 ± 14.0 | 34.0 ± 6.3 | 0.592 | 1.397 ± 0.66 | 2.341 ± 0.95 | 0.940 ± 1.26 | 0.46 | ||
| All | 294 | 95 | 199 | 47.0 ± 15.5 | 33.3 ± 6.9 | 0.686 | 0.351 ± 0.60 | 0.56 | 0.735 ± 0.81 | 0.366 | -0.248 ± 1.29 | 0.85 |
* Standard deviation is shown.
# Standard error is shown.
The linear regression model used to produce effect estimates included age and sex as covariates. In the analysis including all populations, "population" was also included as a covariate. Results for all three modes of inheritance (co-dominant, dominant and recessive) are shown. Statistically significant P values (P < 0.05) are shown in bold.
Figure 1Estimated effects of Gly482Ser SNP on BMI. The solid circles represent the estimate and the whiskers represent the standard errors around each estimate. Estimates were obtained from a linear regression model assuming codominance of the risk allele with age and sex as covariates. In the analysis involving both populations, "population" was also included as a covariate.
Figure 2Worldwide frequency distribution of the 482Ser risk allele. The frequency of the 482Ser risk allele in each population is indicated in black. Frequencies are shown for the 53 populations from the CEPH Human Genome Diversity Panel and 6 additional populations. The raw genotype and allele frequency data for these populations can be found in Additional File 1, Table S1. The populations most relevant to the present study are abbreviated as follows: NGM, New Guinea samples from Myles et al. (2007); NGC, New Guinea samples from the CEPH-HGDP; BGV, Bougainville; TON, Tonga; WSN, Western Samoa and Niue; COK, Cook Islands; MRI, Maori.