A microsatellite polymorphism in IGF1 gene promoter and longevity in a Han Chinese population
https://doi.org/10.1186/1756-0500-3-55
© Zhang et al; licensee BioMed Central Ltd. 2010
Received: 9 September 2009
Accepted: 3 March 2010
Published: 3 March 2010
Abstract
Background
Previous studies have suggested a probable association between the polymorphism of a microsatellite locus located in the promoter of IGF1 (Insulin-like growth factor 1) gene and the serum level of IGF1, as well as many age-related diseases. Based on these results, we hypothesized that this polymorphism may influence longevity in humans. We performed an association study in a Han Chinese population to test this hypothesis.
Findings
We recruited 493 elderly Han Chinese individuals (females ≥ 94; males ≥ 90) and 425 young individuals (controls) from Dujiangyan (Sichuan province, China). The genotype distributions and allele frequencies of the microsatellite site in the elderly and control groups were compared by chi square test.
Our results suggested that there was no association between the microsatellite polymorphism and longevity in our Han Chinese population. However, there were more male persons with 18/21 genotype in elderly group than that in control group (11.11 vs. 5.45%, p = 0.011). As the difference was not significant when corrected by Bonferroni method, we speculate that the 18/21 genotype can not be functional in longevity; however, it may link with the real functional loci as there is a long haplotype block embracing the microsatellite locus.
Conclusions
There was no association between polymorphism of the microsatellite in promoter of IGF1 gene and longevity in our study. Future association studies containing the long haplotype block are deserved and can test our speculation of the potential linkage of 18/21 genotype and functional loci.
Keywords
Background
IGF1 (Insulin-like growth factor 1) plays a number of important roles in the human body. It is involved in physiological processes such as growth, development, and metabolism [1], and has been implicated as a factor in the development of common diseases [2]. Meanwhile, a conserved insulin/IGF1 signal pathway which may affect ageing and longevity is known in E.coli, yeast, drosophila, mice and humans [3–7]. Elucidating the functions of insulin/IGF1 pathway in ageing and longevity is a current hot spot in longevity research [8].
Serum IGF1 levels appear to influence susceptibility to disease, and therefore longevity. For example, people with a high level of circulating IGF1 are more susceptible to cancers, while a low level of circulating IGF1 is a risk factor for cardiovascular diseases, premature atherogenesis, and diabetes [5]. Furthermore, Yang et al. suggested that in humans, a reduced level of serum IGF1 in early adulthood and an increased level in elderly time might be a predictor of high longevity. Meanwhile, the heritability of individual IGF1 level variation is about 50% [9], which implies that IGF1 regulation is genetically determined. Considering the evidence for heritability of longevity [10], perhaps there is a hereditable shift in IGF1 regulation in long-lived people [8].
A cytosine-adenine (CA) repeat polymorphism in IGF1 gene promoter region (1 kilo base pairs upstream from the transcription start site) [11] has been associated with serum IGF1 level [12, 13]. At the same time, many studies have related this microsatellite polymorphism to age-related diseases such as diabetes, cancers, and cardiovascular diseases [14–19]. These results are disputed by several other studies [9, 20–24]. However, they suggest that this microsatellite locus might be a potential functional site for serum IGF1 level regulation, and might therefore function in ageing and longevity. Therefore, exploring the association of this microsatellite polymorphism and longevity is urgent.
To our knowledge there have been no reports on the association between the microsatellite polymorphism and longevity in the Han Chinese people. In this study, we conducted an association study in a Han Chinese population to investigate the potential function of this microsatellite locus in predicting longevity.
Methods
Subjects
Demographics of the study participants
Group | N (Male/Female) | Age (Mean ± SD, years) | Nationality | Range of age (year) |
|---|---|---|---|---|
Elderly | 493 (252/241) | 94.97 ± 3.15 | Han | Male ≥ 90; Female ≥ 94 |
Control | 425 (202/223) | 57.17 ± 9.21 | Han | 32-73 |
All participants indicated informed consent by signing a form after they had been given a clear explanation of the potential risks of the study. This research was approved by the Ethics Committee on human experimentation of Kunming Institute of Zoology, Chinese Academy of Sciences and relevant bodies in Dujiangyan. The study was done in accordance with the Declaration of Helsinki and subsequent amendments.
Genotyping
DNA was extracted from white blood cells in whole blood by the standard phenol/chloroform method. Primers for PCR followed those used in previous study [21]. The forward primer was labeled at the 5'-end with 6-FAM fluorescent dye. PCR reactions each included 20 ng genomic DNA as template, 2.5 μL 10× PCR buffer, 1.0 μL dNTP (2.5 mmol·L-1), 0.5 μL BSA (bovine serum albumin, 200 μg·ml-1), 0.5 μL forward primer (10 pmol·μL-1), 0.5 μL reverse primer (10 pmol·μL-1), 0.125 μL rTaq polymerase (Takara, Dalian, China) and distilled water to a total volume of 25 microliter (μL). Thermocycling parameters included an initial denaturation of 5 min. at 95°C; 35 cycles of: 95°C for 30 s, 62°C for 1 min. and 72°C for 1 min.; and a final extension at 72°C for 10 min. PCR products were denatured and size fractionated on 6% denaturing polyacrylamide gel run on an ABI 3730 automated sequencer (AppliedBiosystems, Foster City, CA). Alleles were read and scored by GeneMapper V4.0 software (ABI Perkin Elmer) using Liz500 as size standard. Alleles were verified artificially twice by two different persons. The number of repeats contained in alleles of different length was confirmed by cloning and sequencing two differently sized PCR products (ie. two alleles). We replicated PCR amplication and genotyping of 30% of the samples, ensuring that replicates were performed by a different researcher. Ambiguous results were confirmed by another PCR and fragment analysis.
Statistical analysis
A test of Hardy Weinberg Equilibrium (HWE) was performed using Genepop 3.4 [25]. The program PHASE v2.1 [26, 27] was used to estimate the haplotype of each individual. Statistical analyses were performed with SPSS (version 13.0, Chicago, IL). Allele distributions and genotype frequencies of the elderly (test) and young (control) groups were compared with Pearson's chi square test, using a two-tailed p value was and considering p < 0.05 to be significant. We used a Bonferroni correction to correct for multiple tests of the same data.
To explore the potential function of this microsatellite locus, we categorized the whole population into three genotype groups depending on owning 2, 1, or no copies of major alleles (19- and 21-repeat): 19/19 (21/21), 19/non (21/non), and non/non. We performed chi square test to compare 1) each genotype to the sum of the other two, 2) the frequencies of three genotypes, and 3) the distribution of major allele (19(21)-allele vs. non) in elderly and control groups in order to detect any potential functions of the major alleles.
Results
In this study, we examined the microsatellite polymorphism in IGF1 gene promoter in 493 elderly individuals (241 females and 252 males) and 425 control individuals (223 females and 202 males). The length range of the microsatellite locus was 17 to 23 repeats (only one person has a 13-repeat allele), and the most common alleles are 19-repeat (39.12%) and 21-repeat (26.14%). The genotype distribution followed Hardy-Weinberg Equilibrium (HWE) in both elderly and control groups, as well as when stratified by gender (p > 0.05).
Allele frequencies of the microsatellite in sampled elderly and control groups.
Allele1 | All | Women | Men | |||
|---|---|---|---|---|---|---|
Elderly(%) | Control(%) | Elderly(%) | Control(%) | Elderly(%) | Control(%) | |
13 | 1(0.10) | 0 | 1(0.21) | 0 | 0 | 0 |
16 | 1(0.10) | 1(0.12) | 0 | 1(0.22) | 1(0.20) | 0 |
17 | 79(8.01) | 68(8.00) | 37(7.68) | 34(7.62) | 42(8.33) | 34(8.42) |
18 | 169(17.14) | 138(16.24) | 80(16.60) | 71(15.92) | 89(17.66) | 67(16.58) |
19 | 380(38.54) | 338(39.76) | 198(41.08) | 173(38.79) | 182(36.11) | 165(40.84) |
20 | 69(7.00) | 54(6.35) | 29(6.02) | 28(6.28) | 40(7.94) | 26(6.44) |
21 | 260(26.37) | 220(25.88) | 124(25.73) | 121(27.13) | 136(26.98) | 99(24.51) |
22 | 23(2.33) | 28(3.29) | 12(2.49) | 15(3.36) | 11(2.18) | 13(3.22) |
23 | 4(0.41) | 2(0.24) | 1(0.21) | 2(0.45) | 3(0.60) | 0 |
24 | 0 | 1(0.12) | 0 | 1(0.22) | 0 | 0 |
p = 0.922 | p = 0.948 | p = 0.455 | ||||
Chi square test results for the genotype distribution and allele frequencies of the 19- and 21-repeat alleles in elderly and control groups.
All | Women | Men | |||||||
|---|---|---|---|---|---|---|---|---|---|
Elderly(%) | Control(%) | P value | Elderly(%) | Control(%) | P value | Elderly(%) | Control(%) | P value | |
Genotype | |||||||||
19-repeat1 | 0.543 | 0.582 | 0.283 | ||||||
19/192 | 69(14.00) | 70(16.47) | 0.297 | 36(14.94) | 33(14.80) | 0.966 | 33(13.10) | 37(18.32) | 0.126 |
19/non2 | 242(49.09) | 198(46.59) | 0.45 | 126(52.28) | 107(47.98) | 0.355 | 116(46.03) | 91(45.05) | 0.835 |
non/non2 | 182(36.92) | 157(36.94) | 0.994 | 79(32.78) | 83(37.22) | 0.316 | 103(40.87) | 74(36.63) | 0.357 |
Allele | |||||||||
19-repeat3 | 380(38.54) | 338(39.76) | 0.592 | 198(41.08) | 173(38.79) | 0.477 | 182(36.11) | 165(40.84) | 0.145 |
non | 606(61.46) | 512(60.24) | 284(58.92) | 273(61.21) | 322(63.89) | 239(59.16) | |||
Genotype | |||||||||
21-repeat4 | 0.31 | 0.88 | 0.082 | ||||||
21/212 | 30(6.09) | 33(7.76) | 0.316 | 15(6.22) | 16(7.17) | 0.682 | 15(5.95) | 17(8.42) | 0.308 |
21/non2 | 200(40.57) | 154(36.24) | 0.179 | 94(39.00) | 89(39.91) | 0.842 | 106(42.06) | 65(32.18) | 0.031 6 |
non/non2 | 263(53.35) | 238(56.00) | 0.421 | 132(54.77) | 118(52.91) | 0.688 | 131(51.98) | 120(59.41) | 0.114 |
Allele | |||||||||
21-repeat5 | 260(26.37) | 220(25.88) | 0.813 | 124(25.73) | 121(27.13) | 0.628 | 136(26.98) | 99(24.50) | 0.397 |
Non | 726(73.63) | 630(74.12) | 358(74.27) | 325(72.87) | 368(73.02) | 305(75.50) | |||
The comparison of genotypes with one 21-repeat allele in male elderly and male control groups
Genotype | Male | ||
|---|---|---|---|
Elderly(%1) | Control(%1) | P value2 | |
173/21 | 14(5.56) | 11(5.45) | 0.716 |
18/21 | 28(11.11) | 11(5.45) | 0.0114 |
19/21 | 42(16.67) | 34(16.83) | 0.591 |
20/21 | 14(5.56) | 7(3.47) | 0.182 |
21/22 | 7(2.78) | 2(0.99) | 0.18 |
21/23 | 1(0.40) | 0 | |
The comparison of haplotype distribution in elderly and control groups.
All | Female | Male | ||||
|---|---|---|---|---|---|---|
Haplotype | Elderly(%) | Control(%) | Elderly(%) | Control(%) | Elderly(%) | Control(%) |
C 131 TT | 1(0.10) | 0 | 1(0.21) | 0 | 0 | 0 |
C 16 TT | 0 | 1(0.12) | 0 | 1(0.23) | 0 | 0 |
C 17 TT | 78(7.99) | 68(8.46) | 37(7.71) | 34(7.91) | 41(8.27) | 34(9.09) |
C 18 TT | 162(16.59) | 125(15.55) | 74(15.42) | 66(15.35) | 88(17.74) | 59(15.78) |
C 19 TT | 357(36.58) | 295(36.69) | 186(38.75) | 150(34.88) | 171(34.48) | 145(38.77) |
C 19 CA | 1(0.10) | 0 | 0 | 0 | 1(0.20) | 0 |
C 20 TT | 28(2.87) | 21(2.61) | 13(2.71) | 12(2.79) | 15(3.02) | 9(2.41) |
C 21 TT | 10(1.02) | 8(1.00) | 1(0.21) | 3(0.70) | 9(1.81) | 5(1.34) |
T 18 CA | 8(0.82) | 3(0.37) | 6(1.25) | 2(0.47) | 2(0.40) | 1(0.27) |
T 19 TT | 12(1.23) | 8(1.00) | 8(1.67) | 5(1.16) | 4(0.81) | 3(0.80) |
T 19 CA | 5(0.51) | 16(1.99) | 2(0.42) | 11(2.56) | 3(0.60) | 5(1.34) |
T 20 TT | 29(2.97) | 22(2.74) | 12(2.50) | 12(2.79) | 17(3.43) | 10(2.67) |
T 20 CA | 10(1.02) | 7(0.87) | 4(0.83) | 3(0.70) | 6(1.21) | 4(1.07) |
T 21 TT | 6(0.61) | 10(1.24) | 2(0.42) | 8(1.86) | 4(0.81) | 2(0.53) |
T 21 CA | 242(24.80) | 186(23.13) | 121(25.21) | 103(23.95) | 121(24.40) | 83(22.19) |
T 22 CA | 23(2.36) | 28(3.48) | 12(2.50) | 15(3.49) | 11(2.22) | 13(3.48) |
T 23 CA | 4(0.41) | 4(0.50) | 1(0.21) | 4(0.93) | 3(0.60) | 0 |
T 24 CA | 0 | 2(0.25) | 0 | 1(0.23) | 0 | 1(0.27) |
Total2 | 976 | 804 | 480 | 430 | 496 | 374 |
P-value | 0.260 | 0.142 | 0.797 | |||
Discussion
In the present study, we explored the association of a microsatellite polymorphism in IGF1 gene promoter with longevity in a Han Chinese population. The elderly and control groups were recruited from the same area. They shared the same living conditions, diet habits, and culture. This allows us to exclude non-genetic factors which may also affect longevity, and ensures that population stratification can be avoided to a certain extent in our study [29]. Additionally, the genotype distributions of both groups did not deviate from HWE.
To our knowledge, this is the first study of the correlation between this microsatellite polymorphism and longevity in a Han Chinese population. The allele distribution of this microsatellite in our population is consistent with a previous study on breast cancer in Chinese people [17]. The distribution is different from that in Caucasian population, as described by Jernstrom et al. [13], demonstrating that allele frequencies at this locus differ between the two populations. This difference may be caused by demographic geography and history of Chinese and Caucasian populations, or by genetic drift. However, within the Han population there is no significant difference in genotypes between elderly and control groups, even when stratified by gender. Our results suggest that no specific alleles at this locus are associated with longevity in this Han population.
To explore the potential role of the microsatellite locus, we compared the genotype frequencies in elderly and control groups depending on 19-repeat and 21-repeat (the two most common alleles) to define categories. As stated in the introduction, the common 19-repeat allele is thought to be related to serum IGF1 levels and many age-related diseases, although the results are equivocal. The contradiction between studies can be explained by different population size, different ethnicities in different studies, and small effect of this polymorphism in complex diseases. Similarly, longevity is a complex trait, influenced by the additive effects of many genetic variations (not to mention stochasticity). Thus an association study may simply not have sufficient power to detect significant correlations between the 19-repeat and longevity.
We initially found a significant difference between the 21-repeat/non genotype frequencies in male elderly (42.06%) and control (32.18%) groups, as well as between the 18/21 genotype (11.11 versus 5.45%, p = 0.011) and other genotypes. However, Bonferroni corrections increased the p values past the cut-off point for statistical significance. Based on these results, the 21-repeat can not be a potential functional allele for male longevity. The 18/21 genotype may still be linked to real functional variations, because in a recent study, a long haplotype block including this microsatellite region was reported [30]. We constructed haplotypes for each participant using our microsatellite and three SNPs data, and found that no single haplotype was positively associated with longevity. The haplotype block is long enough that more SNPs from this region could be included for testing if a potential functional site exists, and we recommend this approach be used before our initial hypothesis is fully rejected., in order to ensure that small sample size (of loci) did not bias the results.
In summary, the results from the present research suggest no association between the microsatellite polymorphism in IGF1 gene promoter and longevity in a Han Chinese population. The possibility of a functional site linked to the microsatellite locus (especially in men) deserves future studies.
Conclusions
In this study, no association was discovered between the microsatellite site in IGF1 gene promoter and longevity in a Han Chinese population. In males, the 18/21 genotype was more frequent in the elderly group than in the control group (11.11 vs. 5.45%, p = 0.011). Future studies including an increased sample size and more loci in the long haplotype block will enable us to test the hypothesized linkage between the 18/21 genotype and functional loci.
Declarations
Acknowledgements
We are grateful to the persons who participated in this research. In addition, we thank Dr. Hui Li, Dr. Cheng-ye Wang, Kristen Choffe and Christina Davy for their help in preparing the manuscript. We would like to acknowledge Shi-fang Wu, Shi-kang Gou, and Chun-ling Zhu for their help in experiments. This work was supported by National Basic Research Program of China (No. 2007CB507405), "Light in Western China" of the Chinese Academy of Sciences, the National Natural Science Foundation of China (30621092), and Bureau of Science and Technology of Yunnan Province.
Authors’ Affiliations
References
- Monzavi R, Cohen P: IGFs and IGFBPs: role in health and disease. Best Pract Res Clin Endocrinol Metab. 2002, 16 (3): 433-447. 10.1053/beem.2002.0212.PubMedView ArticleGoogle Scholar
- Rodriguez S, Gaunt TR, Day IN: Molecular genetics of human growth hormone, insulin-like growth factors and their pathways in common disease. Hum Genet. 2007, 122 (1): 1-21. 10.1007/s00439-007-0378-3.PubMedView ArticleGoogle Scholar
- Kenyon C: A conserved regulatory system for aging. Cell. 2001, 105 (2): 165-168. 10.1016/S0092-8674(01)00306-3.PubMedView ArticleGoogle Scholar
- Tatar M, Bartke A, Antebi A: The endocrine regulation of aging by insulin-like signals. Science. 2003, 299 (5611): 1346-1351. 10.1126/science.1081447.PubMedView ArticleGoogle Scholar
- Yang J, Anzo M, Cohen P: Control of aging and longevity by IGF-I signaling. Exp Gerontol. 2005, 40 (11): 867-872. 10.1016/j.exger.2005.08.001.PubMedView ArticleGoogle Scholar
- Bartke A: Impact of reduced insulin-like growth factor-1/insulin signaling on aging in mammals: novel findings. Aging Cell. 2008, 7: 285-290. 10.1111/j.1474-9726.2008.00387.x.PubMedView ArticleGoogle Scholar
- Jan Vijg YS: Genetics of Longevity and Aging. Annu Rev Med. 2005, 56: 193-212. 10.1146/annurev.med.56.082103.104617.PubMedView ArticleGoogle Scholar
- Bonafe M, Olivieri F: Genetic polymorphism in long-lived people: cues for the presence of an insulin/IGF-pathway-dependent network affecting human longevity. Mol Cell Endocrinol. 2009, 299 (1): 118-123. 10.1016/j.mce.2008.10.038.PubMedView ArticleGoogle Scholar
- Jernstrom H, Deal C, Wilkin F, Chu W, Tao Y, Majeed N, Hudson T, Narod SA, Pollak M: Genetic and nongenetic factors associated with variation of plasma levels of insulin-like growth factor-I and insulin-like growth factor-binding protein-3 in healthy premenopausal women. Cancer Epidemiol Biomarkers Prev. 2001, 10 (4): 377-384.PubMedGoogle Scholar
- Schoenmaker M, de Craen AJ, de Meijer PH, Beekman M, Blauw GJ, Slagboom PE, Westendorp RG: Evidence of genetic enrichment for exceptional survival using a family approach: the Leiden Longevity Study. Eur J Hum Genet. 2006, 14 (1): 79-84.PubMedGoogle Scholar
- Rotwein P, Pollock KM, Didier DK, Krivi GG: Organization and sequence of the human insulin-like growth factor I gene. Alternative RNA processing produces two insulin-like growth factor I precursor peptides. J Biol Chem. 1986, 261 (11): 4828-4832.PubMedGoogle Scholar
- Rosen CJ, Kurland ES, Vereault D, Adler RA, Rackoff PJ, Craig WY, Witte S, Rogers J, Bilezikian JP: Association between serum insulin growth factor-I (IGF-I) and a simple sequence repeat in IGF-I gene: implications for genetic studies of bone mineral density. J Clin Endocrinol Metab. 1998, 83 (7): 2286-2290. 10.1210/jc.83.7.2286.PubMedView ArticleGoogle Scholar
- Jernstrom H, Chu W, Vesprini D, Tao Y, Majeed N, Deal C, Pollak M, Narod SA: Genetic factors related to racial variation in plasma levels of insulin-like growth factor-1: implications for premenopausal breast cancer risk. Mol Genet Metab. 2001, 72 (2): 144-154. 10.1006/mgme.2000.3130.PubMedView ArticleGoogle Scholar
- Vaessen N, Heutink P, Janssen JA, Witteman JC, Testers L, Hofman A, Lamberts SW, Oostra BA, Pols HA, van Duijn CM: A polymorphism in the gene for IGF-I: functional properties and risk for type 2 diabetes and myocardial infarction. Diabetes. 2001, 50 (3): 637-642. 10.2337/diabetes.50.3.637.PubMedView ArticleGoogle Scholar
- Juul A, Scheike T, Davidsen M, Gyllenborg J, Jorgensen T: Low serum insulin-like growth factor I is associated with increased risk of ischemic heart disease: a population-based case-control study. Circulation. 2002, 106 (8): 939-944. 10.1161/01.CIR.0000027563.44593.CC.PubMedView ArticleGoogle Scholar
- Friedrichsen DM, Hawley S, Shu J, Humphrey M, Sabacan L, Iwasaki L, Etzioni R, Ostrander EA, Stanford JL: IGF-I and IGFBP-3 polymorphisms and risk of prostate cancer. Prostate. 2005, 65 (1): 44-51. 10.1002/pros.20259.PubMedView ArticleGoogle Scholar
- Wen W, Gao YT, Shu XO, Yu H, Cai Q, Smith JR, Zheng W: Insulin-like growth factor-I gene polymorphism and breast cancer risk in Chinese women. Int J Cancer. 2005, 113 (2): 307-311. 10.1002/ijc.20571.PubMedView ArticleGoogle Scholar
- Cleveland RJ, Gammon MD, Edmiston SN, Teitelbaum SL, Britton JA, Terry MB, Eng SM, Neugut AI, Santella RM, Conway K: IGF1 CA repeat polymorphisms, lifestyle factors and breast cancer risk in the Long Island Breast Cancer Study Project. Carcinogenesis. 2006, 27 (4): 758-765. 10.1093/carcin/bgi294.PubMedView ArticleGoogle Scholar
- Tsuchiya N, Wang L, Horikawa Y, Inoue T, Kakinuma H, Matsuura S, Sato K, Ogawa O, Kato T, Habuchi T: CA repeat polymorphism in the insulin-like growth factor-I gene is associated with increased risk of prostate cancer and benign prostatic hyperplasia. Int J Oncol. 2005, 26 (1): 225-231.PubMedGoogle Scholar
- Frayling TM, Hattersley AT, McCarthy A, Holly J, Mitchell SM, Gloyn AL, Owen K, Davies D, Smith GD, Ben-Shlomo Y: A putative functional polymorphism in the IGF-I gene: association studies with type 2 diabetes, adult height, glucose tolerance, and fetal growth in U.K. populations. Diabetes. 2002, 51 (7): 2313-2316. 10.2337/diabetes.51.7.2313.PubMedView ArticleGoogle Scholar
- Missmer SA, Haiman CA, Hunter DJ, Willett WC, Colditz GA, Speizer FE, Pollak MN, Hankinson SE: A sequence repeat in the insulin-like growth factor-1 gene and risk of breast cancer. Int J Cancer. 2002, 100 (3): 332-336. 10.1002/ijc.10473.PubMedView ArticleGoogle Scholar
- Li L, Cicek MS, Casey G, Witte JS: No association between genetic polymorphisms in IGF-I and IGFBP-3 and prostate cancer. Cancer Epidemiol Biomarkers Prev. 2004, 13 (3): 497-498.PubMedGoogle Scholar
- Morimoto LM, Newcomb PA, White E, Bigler J, Potter JD: Variation in plasma insulin-like growth factor-1 and insulin-like growth factor binding protein-3: genetic factors. Cancer Epidemiol Biomarkers Prev. 2005, 14 (6): 1394-1401. 10.1158/1055-9965.EPI-04-0694.PubMedView ArticleGoogle Scholar
- Chen C, Freeman R, Voigt LF, Fitzpatrick A, Plymate SR, Weiss NS: Prostate cancer risk in relation to selected genetic polymorphisms in insulin-like growth factor-I, insulin-like growth factor binding protein-3, and insulin-like growth factor-I receptor. Cancer Epidemiol Biomarkers Prev. 2006, 15 (12): 2461-2466. 10.1158/1055-9965.EPI-06-0541.PubMedView ArticleGoogle Scholar
- Raymond M, Rousset F: GENEPOP (Version 1.2): Population Genetics Software for Exact Tests and Ecumenicism. J Hered. 1995, 86 (3): 248-249.Google Scholar
- Stephens M, Smith NJ, Donnelly P: A new statistical method for haplotype reconstruction from population data. Am J Hum Genet. 2001, 68 (4): 978-989. 10.1086/319501.PubMed CentralPubMedView ArticleGoogle Scholar
- Stephens M, Scheet P: Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. Am J Hum Genet. 2005, 76 (3): 449-462. 10.1086/428594.PubMed CentralPubMedView ArticleGoogle Scholar
- Xie L, Gong YY, Lian SG, Yang J, Yang Y, Gao SJ, Xu LY, Zhang YP: Absence of association between SNPs in the promoter region of the insulin-like growth factor 1 (IGF-1) gene and longevity in the Han Chinese population. Exp Gerontol. 2008, 43 (10): 962-965. 10.1016/j.exger.2008.08.004.PubMedView ArticleGoogle Scholar
- Marchini J, Cardon LR, Phillips MS, Donnelly P: The effects of human population structure on large genetic association studies. Nat Genet. 2004, 36 (5): 512-517. 10.1038/ng1337.PubMedView ArticleGoogle Scholar
- Cheng I, Stram DO, Penney KL, Pike M, Le Marchand L, Kolonel LN, Hirschhorn J, Altshuler D, Henderson BE, Freedman ML: Common genetic variation in IGF1 and prostate cancer risk in the Multiethnic Cohort. J Natl Cancer Inst. 2006, 98 (2): 123-134.PubMedView ArticleGoogle Scholar
Copyright
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
