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Am J Hum Genet. 2006 January; 78(1): 130–136. Published online 2005 November 16. | PMCID: PMC1380210 |
Copyright © 2005 by The American Society of Human Genetics. All rights reserved. Variants Associated with Common Disease Are Not Unusually Differentiated in Frequency across Populations Kirk E. Lohmueller,1,3 Matthew M. Mauney,2 David Reich,4,5 and John M. Braverman1 Departments of 1Biology and 2Computer Science, Georgetown University, and 3Institute for Molecular and Human Genetics, Georgetown University Medical Center, Washington, DC; 4Department of Genetics, Harvard Medical School, Boston; and 5Broad Institute of Harvard and MIT, Cambridge, MA Received June 8, 2005; Accepted October 13, 2005. Genetic variants that contribute to risk of common disease may differ in frequency across populations more than random variants in the genome do, perhaps because they have been exposed to population-specific natural selection. To assess this hypothesis empirically, we analyzed data from two groups of single-nucleotide polymorphisms (SNPs) that have shown reproducible (n=9) or reported (n=39) associations with common diseases. We compared the frequency differentiation (between Europeans and Africans) of the disease-associated SNPs with that of random SNPs in the genome. These common-disease–associated SNPs are not significantly more differentiated across populations than random SNPs. Thus, for the data examined here, ethnicity will not be a good predictor of genotype at many common-disease–associated SNPs, just as it is rarely a good predictor of genotype at random SNPs in the genome. An open question in medical and population genetics is how much information a person’s self-identified ancestry (ethnicity) conveys about his or her risk of common disease (Risch et al. 2002; Burchard et al. 2003; Cooper et al. 2003). One way in which ethnicity could be informative about common-disease risk is if risk alleles vary in frequency among populations, which would allow ethnicity to be a predictor of whether a person has a risk allele. This correlation between ethnicity and genotype would be strongest if the disease-associated variants were differentiated in frequency. Although it is known that random variants in the genome are not particularly differentiated across populations on average (Lewontin 1972; Bowcock et al. 1991; Rosenberg et al. 2002), it has been hypothesized that, because of population-specific natural selection, functional SNPs associated with common disease may be more differentiated (Akey et al. 2002; Bamshad et al. 2004). There has been no empirical attempt to address this question, largely because so few disease-associated SNPs have been identified to date. We set out to test the hypothesis that common-disease–associated SNPs are more differentiated than random SNPs by conducting an empirical evaluation of population differentiation in 48 SNPs associated with common disease. We wanted to study SNPs that were associated with common, complex traits, so we explicitly excluded variants associated with Mendelian diseases. The SNPs were all identified in a way that would not create a bias toward unusually high or low levels of frequency differentiation across populations, since each of them was initially identified in studies of single populations. We first studied nine SNPs reproducibly associated with common disease ( table 1). These SNPs satisfied two criteria: (1) >75% of replication studies showed a statistically significant association (Hirschhorn et al. 2002) or the association was significant after meta-analysis of replication studies (Lohmueller et al. 2003) and (2) allele-frequency information was publicly available for the SNPs in both West African and European-derived populations. | Table 1Allele-Frequency Data for Nine Reproducible Associations |
Second, we studied 39 SNPs that have been reported to be associated with common disease ( table 2) but for which association has not necessarily been replicated. These were identified by checking the genes sequenced by the Seattle SNPs project ( Seattle SNPs Web site) for overlap with the SNPs reported to be associated with common disease in the OMIM and PubMed databases or in table 1 of Hirschhorn et al. ( 2002). | Table 2Allele-Frequency Data for 39 Reported Associations |
To assess whether the disease-associated SNPs are more differentiated across populations than random SNPs in the genome, we compared the two groups of disease-associated SNPs with SNPs from two public databases ( table 3). The first database (“WICGR”) was generated by the Whitehead/MIT Center for Genome Research and includes frequency data for SNPs genotyped in European American and Nigerian populations (see The SNP Consortium Allele Frequency/Genotype Project Web site). Since this data set includes a West African population, it was compared to the reproducible-disease-association group. The second database (“Perlegen”) consists of SNPs for which frequency information is available in both European and African American populations (Hinds et al. 2005); it also has the virtue of including genotypes of the same samples that were studied for the Seattle SNPs project. For both databases, the physical map position, gene name, and SNP type were downloaded from dbSNP by a batch query of “rs” numbers (National Center for Biotechnology Information, dbSNP build 120, March 2004). SNPs were excluded from analysis if they were ( a) not polymorphic, ( b) mapped to more than one chromosomal location, or ( c) within 20 kb of each other. The final WICGR data set consisted of 2,377 SNPs, and the final Perlegen data set consisted of 103,536 SNPs. To measure differentiation between European- and African-derived populations for the SNPs in all four data sets, we calculated FST (Weir and Cockerham 1984; Weir 1996), a classic measure of the frequency differentiation of a polymorphism. | Table 3Summary of FST Values for Comparison of Disease-Association and Genomewide Data Sets |
To determine whether the average FST of 0.159 in the group of nine SNPs that were reproducibly associated with common disease was significantly larger than the average for random SNPs in the WICGR data set, we subsampled the WICGR data 10,000 times, counting the proportion of times that nine SNPs randomly chosen from WICGR had an average FST![[gt-or-equal, slanted]](/corehtml/pmc/pmcents/ges.gif) 0.159. We did not find a significant increase in average FST in the reproducible-association set relative to the random group ( P=.12). The same subsampling method also did not detect an excess in the percentage of SNPs with FST>0.3 ( P=.26). To obtain an upper bound on the level of differentiation at common-disease–associated SNPs, we performed bootstrap resamplings of the data from the nine reproducibly associated SNPs. Of 10,000 bootstrap replicates, 95% had average FST values in the range 0.074–0.274, which, as expected, is consistent with the average FST of the random SNPs. A potential concern with this analysis is that different numbers of samples were used to calculate FST for the disease-associated and WICGR data sets. We therefore repeated our analysis after randomly dropping samples from the WICGR data set and the reproducible-disease-association data set until only 72 African and 72 European alleles for each SNP remained. More specifically, for the reproducible-disease-association group, we performed the random sample-dropping procedure for the nine SNPs 1,000 times and recalculated FST for each replicate. The average FST and the percentage of FST values >0.3 in both data sets were extremely similar and were nearly identical to those observed in our original data sets, and we again could not reject the null hypothesis of no difference between the disease-associated and random SNPs ( table 3). We followed an identical protocol to compare FST in the group of SNPs with reported disease association to FST of SNPs in the Perlegen database. Here, there was no problem of sample size or sample mismatch, since the Perlegen set was genotyped in the same European American and African American individuals who were assayed for the disease-associated SNPs by the Seattle SNPs project. We did not find a significant increase in average FST ( P=.13) or in the percentage of SNPs with FST>0.3 ( P=.29) in the reported-disease-association group relative to the Perlegen data set. To obtain a 95% CI for the differentiation, we performed 10,000 bootstrap resamplings of the 39 SNPs. The 95% CI is 0.074–0.171 and includes the genomewide average FST of the Perlegen data set (0.083) ( table 3), which explains why the null hypothesis of no excess differentiation in the disease-associated SNPs relative to the random SNPs cannot be rejected. Because more SNPs are available for the reported-association group than for the reproducible-association group, we were able to put a more stringent upper bound on FST for the reported-association group. Another question in medical genetics is whether disease-associated SNPs in the genome are more differentiated than random nonsynonymous SNPs (Freedman et al. 2004). To test this, we performed an analysis of the reported-association group in comparison with 6,763 nonsynonymous SNPs from the Perlegen data set (which may, of course, include some disease-associated SNPs). We did not find a significant increase in average FST ( P=.06) or in the percentage of SNPs with FST>0.3 ( P=.13) in the reported-disease-association group relative to the nonsynonymous SNPs from the Perlegen data set. The SNPs associated with common disease that we investigated do not show much higher levels of differentiation than those of random SNPs. Thus, in these cases, ethnicity is a poor predictor of an individual’s genotype, which is also the pattern for random variants in the genome. This lends support to the hypothesis that many population differences in disease risk are environmental, rather than genetic, in origin. However, some exceptional SNPs associated with common disease are highly differentiated in frequency across populations, because of either a history of random drift or natural selection. The exceptional SNPs given in tables 1 and 2 are located in AGT, DRD3, ALOX5AP, ICAM1, IL1B, IL4, IL6, IL8, and PON1. Of note, evidence of selection has been observed for AGT (Nakajima et al. 2004), IL4 (Rockman et al. 2003), IL8 (Hull et al. 2001), and PON1 (Allebrandt et al. 2002). Yet, for the vast majority of the common-disease–associated polymorphisms we examined, ethnicity is likely to be a poor predictor of an individual’s genotype. We thank Joel Hirschhorn for helpful discussions and for providing formatted versions of The SNP Consortium data. We also thank Jason Lohmueller and two anonymous reviewers for critical readings of the manuscript. K.E.L. is supported by a Barry Goldwater Scholarship and is a Georgetown-Hughes Undergraduate Research Scholar. D.R. is the recipient of a Burroughs Wellcome Career Development Award in the Biomedical Sciences. The URLs for data presented herein are as follows: Seattle SNPs, http://pga.gs.washington.edu/ (for National Heart, Lung, and Blood Institute Program for Genomic Application, Seattle SNPs, Seattle, WA [July 2004]). Aitman TJ, Cooper LD, Norsworthy PJ, Wahid FN, Gray JK, Curtis BR, McKeigue PM, Kwiatkowski D, Greenwood BM, Snow RW, Hill AV, Scott J (2000) Malaria susceptibility and CD36 mutation. Nature 405:1015–1016 [PubMed] doi: 10.1038/35016636. Akey JM, Zhang G, Zhang K, Jin L, Shriver MD (2002) Interrogating a high-density SNP map for signatures of natural selection. Genome Res 12:1805–1814 [PubMed] doi: 10.1101/gr.631202. Allebrandt KV, Souza RL, Chautard-Freire-Maia EA (2002) Variability of the paraoxonase gene (PON1) in Euro- and Afro-Brazilians. Toxicol Appl Pharmacol 180:151–156 [PubMed] doi: 10.1006/taap.2002.9368. Altshuler D, Hirschhorn JN, Klannemark M, Lindgren CM, Vohl MC, Nemesh J, Lane CR, Schaffner SF, Bolk S, Brewer C, Tuomi T, Gaudet D, Hudson TJ, Daly M, Groop L, Lander ES (2000) The common PPARγ Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet 26:76–80 [PubMed] doi: 10.1038/79216. Bamshad M, Wooding S, Salisbury BA, Stephens JC (2004) Deconstructing the relationship between genetics and race. Nat Rev Genet 5:598–609 [PubMed] doi: 10.1038/nrg1401. Bayley JP, Ottenhoff TH, Verweij CL (2004) Is there a future for TNF promoter polymorphisms? Genes Immun 5:315–329 [PubMed] doi: 10.1038/sj.gene.6364055. Begovich AB, Carlton VE, Honigberg LA, Schrodi SJ, Chokkalingam AP, Alexander HC, Ardlie KG, et al (2004) A missense singlenucleotide polymorphism in a gene encoding a protein tyrosine phosphatase (PTPN22) is associated with rheumatoid arthritis. Am J Hum Genet 75:330–337 [PubMed] Bowcock AM, Kidd JR, Mountain JL, Hebert JM, Carotenuto L, Kidd KK, Cavalli-Sforza LL (1991) Drift, admixture, and selection in human evolution: a study with DNA polymorphisms. Proc Natl Acad Sci USA 88:839–843 [PubMed] Burchard EG, Ziv E, Coyle N, Gomez SL, Tang H, Karter AJ, Mountain JL, Perez-Stable EJ, Sheppard D, Risch N (2003) The importance of race and ethnic background in biomedical research and clinical practice. N Engl J Med 348:1170–1175 [PubMed] doi: 10.1056/NEJMsb025007. Carter AM, Catto AJ, Kohler HP, Ariens RA, Stickland MH, Grant PJ (2000) α-Fibrinogen Thr312Ala polymorphism and venous thromboembolism. Blood 96:1177–1179 [PubMed] Cooper RS, Kaufman JS, Ward R (2003) Race and genomics. N Engl J Med 348:1166–1170 [PubMed] doi: 10.1056/NEJMsb022863. Crocq MA, Buguet A, Bisser S, Burgert E, Stanghellini A, Uyanik G, Dumas M, Macher JP, Mayerova A (1996) BalI and MspI polymorphisms of the dopamine D3 receptor gene in African blacks and Caucasians. Hum Hered 46:58–60 [PubMed] El-Omar EM, Carrington M, Chow WH, McColl KE, Bream JH, Young HA, Herrera J, Lissowska J, Yuan CC, Rothman N, Lanyon G, Martin M, Fraumeni JF Jr, Rabkin CS (2000) Interleukin-1 polymorphisms associated with increased risk of gastric cancer. Nature 404:398–402 [PubMed] doi: 10.1038/35006081. Feder JN, Gnirke A, Thomas W, Tsuchihashi Z, Ruddy DA, Basava A, Dormishian F, et al (1996) A novel MHC class I-like gene is mutated in patients with hereditary haemochromatosis. Nat Genet 13:399–408 [PubMed] doi: 10.1038/ng0896-399. Fernandez-Reyes D, Craig AG, Kyes SA, Peshu N, Snow RW, Berendt AR, Marsh K, Newbold CI (1997) A high frequency African coding polymorphism in the N-terminal domain of ICAM-1 predisposing to cerebral malaria in Kenya. Hum Mol Genet 6:1357–1360 [PubMed] doi: 10.1093/hmg/6.8.1357. Finckh U, van Hadeln K, Muller-Thomsen T, Alberici A, Binetti G, Hock C, Nitsch RM, Stoppe G, Reiss J, Gal A (2003) Association of late-onset Alzheimer disease with a genotype of PLAU, the gene encoding urokinase-type plasminogen activator on chromosome 10q22.2. Neurogenetics 4:213–217 [PubMed] doi: 10.1007/s10048-003-0157-9. Fishman D, Faulds G, Jeffery R, Mohamed-Ali V, Yudkin JS, Humphries S, Woo P (1998) The effect of novel polymorphisms in the interleukin-6 (IL-6) gene on IL-6 transcription and plasma IL-6 levels, and an association with systemic-onset juvenile chronic arthritis. J Clin Invest 102:1369–1376 [PubMed] Florez JC, Burtt N, de Bakker PI, Almgren P, Tuomi T, Holmkvist J, Gaudet D, Hudson TJ, Schaffner SF, Daly MJ, Hirschhorn JN, Groop L, Altshuler D (2004) Haplotype structure and genotype-phenotype correlations of the sulfonylurea receptor and the islet ATP-sensitive potassium channel gene region. Diabetes 53:1360–1368 [PubMed] Freedman ML, Reich D, Penney KL, McDonald GJ, Mignault AA, Patterson N, Gabriel SB, Topol EJ, Smoller JW, Pato CN, Pato MT, Petryshen TL, Kolonel LN, Lander ES, Sklar P, Henderson B, Hirschhorn JN, Altshuler D (2004) Assessing the impact of population stratification on genetic association studies. Nat Genet 36:388–393 [PubMed] doi: 10.1038/ng1333. Gonzalez-Conejero R, Lozano ML, Rivera J, Corral J, Iniesta JA, Moraleda JM, Vicente V (1998) Polymorphisms of platelet membrane glycoprotein Ib associated with arterial thrombotic disease. Blood 92:2771–2776 [PubMed] Heinzmann A, Jerkic SP, Ganter K, Kurz T, Blattmann S, Schuchmann L, Gerhold K, Berner R, Deichmann KA (2003) Association study of the IL13 variant Arg110Gln in atopic diseases and juvenile idiopathic arthritis. J Allergy Clin Immunol 112:735–739 [PubMed] doi: 10.1016/S0091-6749(03)01887-6. Helgadottir A, Manolescu A, Thorleifsson G, Gretarsdottir S, Jonsdottir H, Thorsteinsdottir U, Samani NJ, et al (2004) The gene encoding 5-lipoxygenase activating protein confers risk of myocardial infarction and stroke. Nat Genet 36:233–239 [PubMed] doi: 10.1038/ng1311. Herrmann SM, Ricard S, Nicaud V, Mallet C, Evans A, Ruidavets JB, Arveiler D, Luc G, Cambien F (1998) The P-selectin gene is highly polymorphic: reduced frequency of the Pro715 allele carriers in patients with myocardial infarction. Hum Mol Genet 7:1277–1284 [PubMed] doi: 10.1093/hmg/7.8.1277. Hershey GK, Friedrich MF, Esswein LA, Thomas ML, Chatila TA (1997) The association of atopy with a gain-of-function mutation in the α subunit of the interleukin-4 receptor. N Engl J Med 337:1720–1725 [PubMed] doi: 10.1056/NEJM199712113372403. Hinds DA, Stuve LL, Nilsen GB, Halperin E, Eskin E, Ballinger DG, Frazer KA, Cox DR (2005) Whole-genome patterns of common DNA variation in three human populations. Science 307:1072–1079 [PubMed] doi: 10.1126/science.1105436. Hirschhorn JN, Lohmueller K, Byrne E, Hirschhorn K (2002) A comprehensive review of genetic association studies. Genet Med 4:45–61 [PubMed] Hull J, Ackerman H, Isles K, Usen S, Pinder M, Thomson A, Kwiatkowski D (2001) Unusual haplotypic structure of IL8, a susceptibility locus for a common respiratory virus. Am J Hum Genet 69:413–419 [PubMed] Hull J, Thomson A, Kwiatkowski D (2000) Association of respiratory syncytial virus bronchiolitis with the interleukin 8 gene region in UK families. Thorax 55:1023–1027 [PubMed] doi: 10.1136/thorax.55.12.1023. Iwai C, Akita H, Kanazawa K, Shiga N, Terashima M, Matsuda Y, Takai E, Miyamoto Y, Shimizu M, Kajiya T, Hayashi T, Yokoyama M (2003) Arg389Gly polymorphism of the human β1-adrenergic receptor in patients with nonfatal acute myocardial infarction. Am Heart J 146:106–109 [PubMed] doi: 10.1016/S0002-8703(03)00110-8. Jiang Z, Akey JM, Shi J, Xiong M, Wang Y, Shen Y, Xu X, Chen H, Wu H, Xiao J, Lu D, Huang W, Jin L (2001) A polymorphism in the promoter region of catalase is associated with blood pressure levels. Hum Genet 109:95–98 [PubMed] doi: 10.1007/s004390100553. Koh WP, Yuan JM, van den Berg D, Lee HP, Yu MC (2004) Interaction between cyclooxygenase-2 gene polymorphism and dietary n-6 polyunsaturated fatty acids on colon cancer risk: the Singapore Chinese Health Study. Br J Cancer 90:1760–1764 [PubMed] Kohler HP, Futers TS, Grant PJ (1999) Prevalence of three common polymorphisms in the A-subunit gene of factor XIII in patients with coronary artery disease. Thromb Haemost 81:511–515 [PubMed] Lahti M, Lofgren J, Marttila R, Renko M, Klaavuniemi T, Haataja R, Ramet M, Hallman M (2002) Surfactant protein D gene polymorphism associated with severe respiratory syncytial virus infection. Pediatr Res 51:696–699 [PubMed] doi: 10.1203/01.PDR.0000015911.65104.93. Lewontin RC (1972) The apportionment of human diversity. Evol Biol 6:381–398. Lin Z, Pearson C, Chinchilli V, Pietschmann SM, Luo J, Pison U, Floros J (2000) Polymorphisms of human SP-A, SP-B, and SP-D genes: association of SP-B Thr131Ile with ARDS. Clin Genet 58:181–191 [PubMed] doi: 10.1034/j.1399-0004.2000.580305.x. Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN (2003) Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet 33:177–182 [PubMed] doi: 10.1038/ng1071. Merryweather-Clarke AT, Pointon JJ, Shearman JD, Robson KJ (1997) Global prevalence of putative haemochromatosis mutations. J Med Genet 34:275–278 [PubMed] Moshfegh K, Wuillemin WA, Redondo M, Lammle B, Beer JH, Liechti-Gallati S, Meyer BJ (1999) Association of two silent polymorphisms of platelet glycoprotein Ia/IIa receptor with risk of myocardial infarction: a case-control study. Lancet 353:351–354 [PubMed] doi: 10.1016/S0140-6736(98)06448-4. Nakajima T, Jorde LB, Ishigami T, Umemura S, Emi M, Lalouel JM, Inoue I (2002) Nucleotide diversity and haplotype structure of the human angiotensinogen gene in two populations. Am J Hum Genet 70:108–123 [PubMed] Nakajima T, Wooding S, Sakagami T, Emi M, Tokunaga K, Tamiya G, Ishigami T, Umemura S, Munkhbat B, Jin F, Guan-Jun J, Hayasaka I, Ishida T, Saitou N, Pavelka K, Lalouel JM, Jorde LB, Inoue I (2004) Natural selection and population history in the human angiotensinogen gene (AGT): 736 complete AGT sequences in chromosomes from around the world. Am J Hum Genet 74:898–916 [PubMed] Nejentsev S, Laaksonen M, Tienari PJ, Fernandez O, Cordell H, Ruutiainen J, Wikstrom J, Pastinen T, Kuokkanen S, Hillert J, Ilonen J (2003) Intercellular adhesion molecule-1 K469E polymorphism: study of association with multiple sclerosis. Hum Immunol 64:345–349 [PubMed] doi: 10.1016/S0198-8859(02)00825-X. Nicoll JA, Mrak RE, Graham DI, Stewart J, Wilcock G, MacGowan S, Esiri MM, Murray LS, Dewar D, Love S, Moss T, Griffin WS (2000) Association of interleukin-1 gene polymorphisms with Alzheimer’s disease. Ann Neurol 47:365–368 [PubMed] doi: 10.1002/1531-8249(200003)47:3<365::AID-ANA13>3.0.CO;2-G. Noguchi E, Shibasaki M, Arinami T, Takeda K, Yokouchi Y, Kawashima T, Yanagi H, Matsui A, Hamaguchi H (1998) Association of asthma and the interleukin-4 promoter gene in Japanese. Clin Exp Allergy 28:449–453 [PubMed] doi: 10.1046/j.1365-2222.1998.00256.x. Norlund L, Holm J, Zoller B, Ohlin AK (1997) A common thrombomodulin amino acid dimorphism is associated with myocardial infarction. Thromb Haemost 77:248–251 [PubMed] Osei-Hyiaman D, Hou L, Zhiyin R, Zhiming Z, Yu H, Amankwah AA, Harada S (2001) Association of a novel point mutation (C159G) of the CTLA4 gene with type 1 diabetes in West Africans but not in Chinese. Diabetes 50:2169–2171 [PubMed] Ozaki K, Ohnishi Y, Iida A, Sekine A, Yamada R, Tsunoda T, Sato H, Hori M, Nakamura Y, Tanaka T (2002) Functional SNPs in the lymphotoxin-α gene that are associated with susceptibility to myocardial infarction. Nat Genet 32:650–654 [PubMed] doi: 10.1038/ng1047. Ray JG, Shmorgun D, Chan WS (2002) Common C677T polymorphism of the methylenetetrahydrofolate reductase gene and the risk of venous thromboembolism: meta-analysis of 31 studies. Pathophysiol Haemost Thromb 32:51–58 [PubMed] doi: 10.1159/000065076. Rees DC, Cox M, Clegg JB (1995) World distribution of factor V Leiden. Lancet 346:1133–1134 [PubMed] doi: 10.1016/S0140-6736(95)91803-5. Risch N, Burchard E, Ziv E, Tang H (2002) Categorization of humans in biomedical research: genes, race, and disease. Genome Biol 3:2007.1–2007.12 [PubMed] Rockman MV, Hahn MW, Soranzo N, Goldstein DB, Wray GA (2003) Positive selection on a human-specific transcription factor binding site regulating IL4 expression. Curr Biol 13:2118–2123 [PubMed] doi: 10.1016/j.cub.2003.11.025. Rosenberg NA, Pritchard JK, Weber JL, Cann HM, Kidd KK, Zhivotovsky LA, Feldman MW (2002) Genetic structure of human populations. Science 298:2381–2385 [PubMed] doi: 10.1126/science.1078311. Rotimi C, Puras A, Cooper R, McFarlane-Anderson N, Forrester T, Ogunbiyi O, Morrison L, Ward R (1996) Polymorphisms of renin-angiotensin genes among Nigerians, Jamaicans, and African Americans. Hypertension 27:558–563 [PubMed] Sanghera DK, Aston CE, Saha N, Kamboh MI (1998) DNA polymorphisms in two paraoxonase genes (PON1 and PON2) are associated with the risk of coronary heart disease. Am J Hum Genet 62:36–44 [PubMed] Schneider JA, Rees DC, Liu YT, Clegg JB (1998) Worldwide distribution of a common methylenetetrahydrofolate reductase mutation. Am J Hum Genet 62:1258–1260 [PubMed] Serrato M, Marian AJ (1995) A variant of human paraoxonase/arylesterase (HUMPONA) gene is a risk factor for coronary artery disease. J Clin Invest 96:3005–3008 [PubMed] Shimasaki Y, Yasue H, Yoshimura M, Nakayama M, Kugiyama K, Ogawa H, Harada E, Masuda T, Koyama W, Saito Y, Miyamoto Y, Ogawa Y, Nakao K (1998) Association of the missense Glu298Asp variant of the endothelial nitric oxide synthase gene with myocardial infarction. J Am Coll Cardiol 31:1506–1510 [PubMed] doi: 10.1016/S0735-1097(98)00167-3. Smith MW, Dean M, Carrington M, Winkler C, Huttley GA, Lomb DA, Goedert JJ, O'Brien TR, Jacobson LP, Kaslow R, Buchbinder S, Vittinghoff E, Vlahov D, Hoots K, Hilgartner MW, Hemophilia Growth and Development Study (HGDS), Multicenter AIDS Cohort Study (MACS), Multicenter Hemophilia Cohort Study (MHCS), San Francisco City Cohort (SFCC), ALIVE Study, O’Brien SJ (1997) Contrasting genetic influence of CCR2 and CCR5 variants on HIV-1 infection and disease progression. Science 277:959–965 [PubMed] doi: 10.1126/science.277.5328.959. Soldevila M, Calafell F, Andres AM, Yague J, Helgason A, Stefansson K, Bertranpetit J (2003) Prion susceptibility and protective alleles exhibit marked geographic differences. Hum Mutat 22:104–105 [PubMed] doi: 10.1002/humu.9157. Takei T, Iida A, Nitta K, Tanaka T, Ohnishi Y, Yamada R, Maeda S, Tsunoda T, Takeoka S, Ito K, Honda K, Uchida K, Tsuchiya K, Suzuki Y, Fujioka T, Ujiie T, Nagane Y, Miyano S, Narita I, Gejyo F, Nihei H, Nakamura Y (2002) Association between single-nucleotide polymorphisms in selectin genes and immunoglobulin A nephropathy. Am J Hum Genet 70:781–786 [PubMed] Taylor JG VI, Tang DC, Savage SA, Leitman SF, Heller SI, Serjeant GR, Rodgers GP, Chanock SJ (2002) Variants in the VCAM1 gene and risk for symptomatic stroke in sickle cell disease. Blood 100:4303–4309 [PubMed] doi: 10.1182/blood-2001-12-0306. Thye T, Burchard GD, Nilius M, Muller-Myhsok B, Horstmann RD (2003) Genomewide linkage analysis identifies polymorphism in the human interferon-γ receptor affecting Helicobacter pylori infection. Am J Hum Genet 72:448–453 [PubMed] Topol EJ, McCarthy J, Gabriel S, Moliterno DJ, Rogers WJ, Newby LK, Freedman M, Metivier J, Cannata R, O’Donnell CJ, Kottke-Marchant K, Murugesan G, Plow EF, Stenina O, Daley GQ (2001) Single nucleotide polymorphisms in multiple novel thrombospondin genes may be associated with familial premature myocardial infarction. Circulation 104:2641–2644 [PubMed] Valverde P, Healy E, Jackson I, Rees JL, Thody AJ (1995) Variants of the melanocyte-stimulating hormone receptor gene are associated with red hair and fair skin in humans. Nat Genet 11:328–330 [PubMed] doi: 10.1038/ng1195-328. van der Pouw Kraan TC, van Veen A, Boeije LC, van Tuyl SA, de Groot ER, Stapel SO, Bakker A, Verweij CL, Aarden LA, van der Zee JS (1999) An IL-13 promoter polymorphism associated with increased risk of allergic asthma. Genes Immun 1:61–65 [PubMed] doi: 10.1038/sj.gene.6363630. Weir BS (1996) Genetic data analysis II. Sinauer, Sunderland, MA. Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358–1370. Wenzel K, Felix S, Kleber FX, Brachold R, Menke T, Schattke S, Schulte KL, Glaser C, Rohde K, Baumann G (1994) E-selectin polymorphism and atherosclerosis: an association study. Hum Mol Genet 3:1935–1937 [PubMed] Yamada R, Tanaka T, Unoki M, Nagai T, Sawada T, Ohnishi Y, Tsunoda T, Yukioka M, Maeda A, Suzuki K, Tateishi H, Ochi T, Nakamura Y, Yamamoto K (2001) Association between a single-nucleotide polymorphism in the promoter of the human interleukin-3 gene and rheumatoid arthritis in Japanese patients, and maximum-likelihood estimation of combinatorial effect that two genetic loci have on susceptibility to the disease. Am J Hum Genet 68:674–685 [PubMed] Zhang P, Yang Z, Zhang C, Lu Z, Shi X, Zheng W, Wan C, Zhang D, Zheng C, Li S, Jin F, Wang L (2003) Association study between late-onset Alzheimer’s disease and the transferrin gene polymorphisms in Chinese. Neurosci Lett 349:209–211 [PubMed] doi: 10.1016/S0304-3940(03)00837-1.
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