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Immunogenetics (2007) 59:839852 DOI 10.1007/s00251-007-0253-3 ORIGINAL PAPER Genotype frequency and FST analysis of polymorphisms in immunoregulatory genes in Chinese and Caucasian populations Qing Lan & Min Shen & Dino Garcia-Rossi & Stephen Chanock & Tongzhang Zheng & Sonja I. Berndt & Vinita Puri & Guilan Li & Xingzhou He & Robert Welch & Shelia H. Zahm & Luoping Zhang & Yawei Zhang & Martyn Smith & Sophia S. Wang & Brian C.-H. Chiu & Martha Linet & Richard Hayes & Nathaniel Rothman & Meredith Yeager Received: 5 June 2007 / Accepted: 11 September 2007 / Published online: 16 October 2007 # Springer-Verlag 2007 Abstract Selection and genetic drift can create genetic differences between populations. Cytokines and chemokines play an important role in both hematopoietic development and the inflammatory response. We compared the genotype frequencies of 45 SNPs in 30 cytokine and chemokine genes in two healthy Chinese populations and one Caucasian population. Several SNPs in IL4 had substantial genetic differentiation between the Chinese and Caucasian populations (FST ~0.40), and displayed a strikingly different haplotype distribution. To further characterize common genetic variation in worldwide populations at the IL4 locus, we genotyped 9 SNPs at the IL4 gene in the Human Diversity Panel's (N=1056) individuals from 52 world geographic regions. We observed low haplotype diversity, yet strikingly different haplotype frequencies between non-African populations, which may indicate different selective pressures on the IL4 gene in different parts of the world. SNPs in CSF2, IL6, IL10, CTLA4, and CX3CR1 showed moderate genetic differentiation between the Chinese and Caucasian populations (0.15<FST<0.25). These results suggest that there is substantial genetic diversity in immune genes and exploration of SNP associations with immune-related diseases that vary in incidence across these two populations may be warranted. Q. V. R. PHLuaarnyie::sRM:.N.WS. heRelconhth::mDSa..nGH:a.MrZci.aahY-Rmeao:gsSseir.:SS..WCahnagno:cMk .: LSi.nIe.tB: erndt : Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA T. Zheng : Y. Zhang Department of Epidemiology and Public Health, Yale School of Medicine, New Haven, CT, USA L. Zhang : M. Smith School of Public Health, University of California, Berkeley, CA, USA G. Li Institute of Occupational Health and Poison Control, China Center of Disease Control and Prevention, Beijing, China X. He Institute of Environmental Health and Engineering, Chinese Center for Disease Control and Prevention, Beijing, China B. C.-H. Chiu Department of Preventive Medicine, Northwestern University Medical School, Chicago, IL, USA M. Yeager (*) Core Genotyping Facility, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 8717 Grovemont Circle, Gaithersburg, MD, China e-mail: yeagerm@mail.nih.gov 840 Immunogenetics (2007) 59:839852 Keywords Genotype frequency . FST . Genetic diversity . Cytokine genes . Chinese . Caucasians Introduction There is increasing evidence that cytokines, chemokines, and other immunomodulatory genes play an important role in hematopoietic development and in the inflammatory response (Farrar et al. 1989; O'Shea et al. 2002). Multiple studies have reported associations between single nucleotide polymorphisms (SNPs) in cytokine and chemokine genes and a wide range of diseases, such as asthma, atopy, progression of HIV infection, inflammatory bowel disease, lupus erythematosus, Alzheimer's disease, and cancer risk even though most still require replication. (Burchard et al. 1999; Lio et al. 2006; Qi et al. 2007; Reiche et al. 2007; Rothman et al. 2006; Thompson and Humphries 2007). The incident rates for some of these diseases vary substantially between different ethnic groups. For example, the incident rate of non-Hodgkin lymphoma (NHL) is relatively low among Asians and considerably higher among Caucasians (Hartge et al. 1994). Furthermore, there are marked ethnic differences in the incidence rates of particular NHL histologic subtypes, such as follicular lymphoma (Biagi and Seymour 2002; Hartge et al. 1994). As such, it is plausible that differences in disease rates across ethnic groups might be explained, at least in part, by differences in allele frequencies for disease-associated SNPs. Human allele frequencies for many genetic variants differ by geographical regions (Ma et al. 2005; Nakajima et al. 2006; Sivakova et al. 2006). These geographic differences of allele frequency among various populations are considered to be the result of several factors including Table 1 Cytokine and chemokine genes and single nucleotide polymorphisms evaluated in three populations a Additional IL4 SNPs genotyped in the Human Diversity Panel. Gene Name Location SNP rs number CCR5 Chemokine, CC motif, receptor 5 3p21 rs2734648 CSF2 Colony stimulating factor 2 5q31.1 rs1469149, rs25882 (granulocyte-macrophage) CX3CR1 Chemokine, CXC motif 3p21 rs3732379 CXCL12 Chemokine, CXC motif, ligand 12 10q11.1 rs1801157 FCGR2A Receptor for Fc fragment of IgG, 1q21-q23 rs1801274 low affinity IIa (CD32) ICAM1 Intercellular adhesion molecule 1 (CD54) 19p13.3-p13.2 rs5491 IFNG Interferon, gamma 21q14 rs1861494 IFNGR2 Interferon, gamma, receptor 2 21q22,10q22.2 rs9808753 IL1A Interleukin 1-alpha 2q13 rs17561, rs1800587 IL1B Interleukin 1-beta 2q14 rs1143627 IL1RN Interleukin 1 receptor antagonist 2q14.2 rs454078 IL2 Interleukin 2 4q26q27 rs2069762 IL4 Interleukin 4 5q31.1 rs2243250, rs2243248; rs2070874, rs2243290, rs2243268, rs2243247a, rs2243251 a, rs2243267 a, rs2243270 a, rs2243289a, IL4R Interleukin 4 receptor 16p12.1p11.2 rs2107356 IL5 Interleukin 5 5q31.1 rs2069812 IL6 Interleukin 6 7p15.3 rs1800795 IL8 Interleukin 8 4q12-q13 rs4073, rs2227307, rs2227306 IL8RA Interleukin 8 receptor, alpha 2q35 rs2234671 IL8RB Interleukin 8 receptor, beta 2q35 rs1126580 IL10 Interleukin 10 1q31q32 rs1800871, rs3024509, rs3024496, rs3024491, rs1800890 IL12A Interleukin 12, alpha 3q25.33 rs568408 IL12B Interleukin 12B 5q33.3 rs3212227 IL13 Interleukin 13 5q23.3 rs20541, rs1800925, rs1295686 IL15RA Interleukin 15 receptor, alpha 10p15.1 rs2296135 LTA Lymphotoxin-alpha 6p21.3 rs909253 MIF Macrophage migration inhibitory factor 22q11.23 rs755622 TGFB1 Transforming growth factor, beta 1 19q13.113.2 rs1800469 TLR4 Toll-like receptor 4 9q32-q33 rs4986790 TNF Tumor necrosis factor 6p21.3 rs1800629, rs1799724 VCAM1 Vascular cell adhesion molecule 1 1p32-p31 rs3176879 Immunogenetics (2007) 59:839852 841 natural selection and neutral genetic drift. In some instances, the functional consequences of specific genetic variants can lead to a more favorable response to environmental factors such as infectious organisms and environmental toxins. As a result, a subset of genetic variants could be under differential selective pressure. The selective pressures exerted by these environmental factors may lead to differences in allele frequencies between populations, particularly populations in which the environmental pressures differ, resulting in significantly higher frequencies among some populations and more than what would be expected from neutral drift. We hypothesized that the frequency of SNPs in key cytokine, chemokine, and other immunoregulatory genes that have been associated with a spectrum of immune-mediated diseases could vary across different continental populations. To test this hypothesis, we compared the genotype frequencies of 45 SNPs in 30 cytokine and chemokine genes from two healthy Chinese populations and one Caucasian population, and 9 SNPs spanning the IL4 gene in the Human Diversity Panel. The SNPs analyzed in this study were selected on the basis of prior functional data in previous association studies or to help characterize the haplotype structure of the gene of interest and the availability of the assay for the previous studies. Materials and methods Data for the primary analyses were drawn from three different studies: (1) n=113 controls of a case-control study of lung cancer (southern Chinese) (Lan et al. 2004a), (2) n= 390 subjects of a cross-sectional study of occupational benzene exposure (northern Chinese) (Lan et al. 2004b, 2005), and 3) n=547 controls of a case-control study of NHL (non-Hispanic Caucasian women living in Connecticut, USA) (Lan et al. 2006). The southern Chinese population was derived from a population-based case-control study (Lan et al. 2000). In brief, this study was conducted between March 1995 and March 1996 in Xuan Wei, China. A control was selected for each lung cancer case matching on sex, age (2 years), village, and type of fuel used currently for cooking and heating at home by a stratified random sampling scheme. A total of 122 controls were enrolled in this study. The participation rate of the controls was 100%. Each subject provided a sample of buccal cells and sputum for genotyping. DNA was extracted from sputum samples using phenolchloroform extraction (Lan et al. 2000). DNA was available from 113 controls for the analyses presented here. Quality control duplicate samples had concordance rates >99% for all assays. The northern Chinese population was drawn from a cross-sectional study of 250 workers exposed to benzene in two shoe manufacturing factories and 140 unexposed controls from three clothes-manufacturing factories in the same region of Tianjin, China (Lan et al. 2004b). Briefly, the unexposed workers were frequency-matched by sex and age to exposed workers. The participation rate was approximately 95%. This was a relatively young, working population. Although this sample set does not represent a random sample of the population, genotype frequencies in this group should approximate genotype frequencies in this region of China because workers were drawn from a broad area across this region. Blood samples were collected from 88 workers in June, 2000 during the first phase of the study and from the remaining workers (28 subjects enrolled in the first phase) in May and June, 2001. Blind replicate samples randomly interspersed throughout the study sample plates had concordance rates >98% for all assays. The Caucasian population was drawn from a populationbased case-control study conducted among women in Connecticut from 1995 to 2001 (Lan et al. 2006; Morton et al. 2003; Zhang et al. 2004). The controls were enrolled from one of two populations: (1) Women who were less than 65 years old were enrolled by random digit dialing; or (2) Women who were 65 years or older were randomly recruited based on Health Care Financing Administration files. Controls were frequency matched on age (5years) to cases with a participation rate of 69% for women less than 65 years old and 47% for women 65 years or older. About 75% (535/717) of interviewed controls provided blood samples. The data presented in this paper were genotyped from blood-derived DNA only. Quality control samples had concordance rates at or above 97% for all assays. For follow-up studies at the IL4 locus, DNA from the Human Diversity Panel (HDP) comprised of N=1,056 individuals (CEPH; Paris, France) (Cann et al. 2002). The HDP can be divided into seven general geographic regions: Africans, Europeans, Western Asians, Central and Southern Asians, Eastern Asians, Oceanians, and Native Americans, with each group containing 7, 8, 3, 9, 18, 2, and 5 representative groups, respectively. For comparative purposes, Table 2 Characteristics of study participants Parameter Northern Chinese Southern Chinese Caucasians n=390 (%) n=113 (%) n=547 (%) Sex Male 138 (35) Female 252 (65) Ethnicity Han Chinese 390 (100) Caucasians Age (MeanSD) 309 73 (65) 40 (35) 113 (100) 55 12 0 547 (100) 547 (100) 62 14 842 Immunogenetics (2007) 59:839852 Table 3 Genotype frequencies Cytokine and chemokine genes in Chinese and Caucasian populations Genotypes Southern Chinese Northern Chinese S. vs N. Chinese P value Chinese Caucasians Chinese vs. Caucasian P value CCR5 rs2734648 IVS1+151G>T GG 27 (25) 95 (24) TG 53 (49) 190 (49) TT 29 (27) 104 (27) CSF2 rs1469149 -674A>C AA 92 (95) 340 (95) AC 5 (5) 17 (5) CC CSF2 rs25882 Ex4+23T>C CC 42 (38) 135 (35) TC 53 (48) 192 (49) TT 15 (14) 61 (16) CX3CR1 rs3732379 Ex2+754G>A AA GA 7 (6) 27 (7) GG 106 (94) 360 (93) CXCL12 rs1801157 Ex4+535C>T AA 9 (8) 14 (4) GA 46 (41) 144 (38) GG 58 (51) 225 (59) FCGR2A rs1801274 Ex4-120A>G AA 54 (49) 156 (41) GA 47 (42) 186 (49) GG 10 (9) 39 (10) ICAM1 rs5491 Ex2+100A>T AA 92 (81) 333 (86) TA 19 (17) 54 (14) TT 2 (2) 1 (0) IFNG rs1861494 IVS3+284G>A AA 50 (44) 143 (38) AG 49 (43) 189 (51) GG 14 (12) 40 (11) IFNGR2 rs9808753 Ex2-16A>G AA 36 (33) 117 (30) GA 56 (51) 200 (52) GG 18 (16) 71 (18) IL1A rs17561 Ex5+21G>T GG 93 (84) 323 (83) TG 18 (16) 60 (15) TT 6 (2) IL1A rs1800587 Ex1+12C>T CC 94 (84) 324 (84) TC 18 (16) 58 (15) TT 5 (1) IL1B rs1143627 -580C>T CC 21 (19) 85 (22) TC 50 (45) 177 (46) TT 40 (36) 125 (32) IL1RN rs454078 IVS6+59A>T AA 95 (86) 322 (83) TA 14 (13) 63 (16) TT 2 (2) 2 (1) IL2 rs2069762 Ex2T>G GG 7 (6) 47 (12) TG 45 (40) 174 (45) TT 60 (54) 166 (43) 1.0 0.87 0.76 0.77 0.1 0.35 0.13 0.38 0.75 0.42 0.47 0.69 0.28 0.078 122 (25) 243 (49) 133 (27) 198 (41) 218 (45) 65 (14) <0.0001 432 (95) 22 (5) 159 (38) 194 (46) 66 (16) <0.0001 177 (36) 245 (49) 76 (15) 22 (5) 165 (34) 296 (61) <0.0001 34 (7) 466 (93) 48 (10) 193 (40) 246 (51) <0.0001 23 (5) 190 (38) 283 (57) 25 (5) 152 (31) 308 (64) 0.073 210 (43) 233 (47) 49 (10) 225 (47) 212 (44) 46 (10) 0.47 424 (85) 73 (15) 3 (1) 486 (100) 1 (0) <0.0001 193 (40) 238 (49) 54 (11) 248 (9) 199 (41) 44 (51) <0.0001 153 (31) 256 (52) 88 (18) 377 (78) 100 (21) 6 (1) <0.0001 416 (83) 78 (16) 6 (1) 244 (50) 204 (42) 37 (8) <0.0001 417 (84) 76 (15) 5 (1) 247 (53) 179 (38) 42 (9) <0.0001 106 (21) 227 (46) 165 (33) 60 (12) 204 (42) 220 (45) <0.0001 417 (84) 77 (15) 4 (1) 272 (59) 151 (33) 36 (8) <0.0001 54 (11) 219 (44) 225 (45) 44 (9) 183 (39) 244 (52) 0.12 Immunogenetics (2007) 59:839852 843 Table 3 (continued) Genotypes Southern Chinese Northern Chinese S. vs N. Chinese P value Chinese IL4 rs2243250 -588C>T CC 2 (2) 17 (4) TC 36 (32) 142 (37) TT 73 (66) 228 (59) IL4 rs2243248 Ex2T>G GG GT 7 (6) 50 (13) TT 103 (94) 338 (87) IL4 rs2070874 Ex1-168C>T CC 5 (4) 23 (6) TC 53 (47) 134 (35) TT 55 (49) 231 (60) IL4 rs2243290 IVS3-9A>C AA 80 (71) 224 (58) AC 31 (28) 142 (37) CC 1 (1) 18 (5) IL4 rs2243268 IVS2-1443A>C AA 1 (1) 17 (4) CA 33 (30) 142 (37) CC 77 (69) 230 (59) IL4R rs2107356 -28120T>C CC 41 (37) 166 (43) TC 57 (51) 161 (41) TT 14 (13) 61 (16) IL5 rs2069812 -745C>T CC 9 (8) 47 (12) TC 46 (41) 146 (38) TT 58 (51) 194 (50) IL6 rs1800795 -236C>G CC CG 1 (1) 13 (3) GG 110 (99) 377 (97) IL8 rs4073 -351A>T AA 15 (13) 61 (16) AT 49 (44) 194 (50) TT 48 (43) 134 (34) IL8 rs2227307 IVS1+230G>T GG 16 (14) 60 (15) TG 49 (44) 194 (50) TT 47 (42) 134 (35) IL8 rs2227306 IVS1-204C>T CC 47 (43) 159 (42) TC 48 (43) 174 (46) TT 15 (14) 49 (13) IL8 RA rs2234671 Ex2+860C>G CC 5 (1) CG 20 (18) 82 (21) GG 92 (82) 301 (78) IL8RB rs1126580 Ex3-1010G>A AA 4 (4) 27 (7) GA 34 (31) 157 (40) GG 71 (65) 204 (53) IL10 rs1800871 -7334T>C CC 9 (8) 49 (13) TC 50 (45) 170 (44) TT 51 (47) 167 (43) 0.24 0.058 0.057 0.02 0.064 0.21 0.45 0.17 0.31 0.4 0.95 0.34 0.055 0.43 19 (4) 177 (36) 301 (61) 57 (11) 441 (89) 28 (6) 187 (37) 286 (57) 304 (61) 173 (35) 19 (4) 18 (4) 175 (35) 307 (61) 207 (41) 218 (44) 75 (15) 56 (11) 192 (38) 252 (54) 14 (3) 486 (97) 76 (15) 243 (49) 181 (36) 76 (15) 243 (49) 180 (36) 205 (42) 222 (45) 64 (13) 5 (1) 102 (20) 393 (79) 31 (6) 191 (38) 275 (55) 58 (12) 219 (44) 218 (44) Caucasians Chinese vs. Caucasian P value 353 (73) 115 (24) 18 (4) 2 (0) 52 (11) 432 (89) 356 (74) 107 (22) 20 (4) 16 (3) 115 (23) 359 (73) 358 (73) 116 (24) 16 (3) 162 (34) 228 (48) 87 (18) 245 (50) 211 (43) 30 (6) 69 (14) 233 (48) 183 (38) 83 (17) 245 (50) 158 (33) 89 (19) 232 (49) 156 (33) 174 (36) 232 (48) 75 (16) 2 (0) 49 (10) 440 (90) 106 (22) 248 (51) 132 (27) 284 (58) 176 (36) 26 (5) <0.0001 0.34 <0.0001 <0.0001 <0.0001 0.048 <0.0001 <0.0001 0.43 0.29 0.17 <0.0001 <0.0001 <0.0001 844 Immunogenetics (2007) 59:839852 Table 3 (continued) Genotypes Southern Chinese Northern Chinese S. vs N. Chinese P value Chinese Caucasians Chinese vs. Caucasian P value IL10 rs3024509 IVS3-58C>T CC TC 1 (0) TT 112 (100) 382 (100) IL10 rs3024496 Ex5+210C>T CC TC 8 (7) 32 (8) TT 105 (93) 356 (92) IL10 rs3024491 IVS1-286G>T GG 105 (93) 354 (91) TG 8 (7) 33 (9) TT IL10 rs1800890 -3584T>A AA TA 22 (6) TT 347 (94) IL12A rs568408 Ex7+277A>G AA 1 (1) 6 (2) AG 31 (27) 73 (19) GG 81 (72) 305 (79) IL12B rs3212227 Ex8+159A>C AA 40 (36) 133 (35) CA 53 (47) 193 (50) CC 19 (17) 58 (15) IL13 rs20541 Ex4+98A>G AA 8 (7) 40 (10) AG 46 (42) 166 (43) GG 54 (50) 180 (47) IL13 rs1800925 -1069C>T CC 86 (77) 287 (74) TC 25 (22) 90 (23) TT 1 (1) 12 (3) IL13 rs1295686 IVS3-24T>C CC 56 (50) 178 (46) TC 48 (43) 170 (44) TT 8 (7) 40 (10) IL15RA rs2296135 Ex8-361A>C GG 17 (15) 66 (17) TG 57 (51) 191 (49) TT 38 (34) 132 (34) LTA rs909253 IVS1+90G>A AA 31 (30) 151 (39) GA 53 (50) 200 (52) GG 22 (20) 37 (10) MIF rs755622 -269G>C CC 5 (5) 16 (4) GC 37 (34) 142 (37) GG 67 (61) 229 (59) TGFB1 rs1800469 -509C>T CC 29 (27) 109 (29) TC 48 (45) 174 (46) TT 30 (28) 92 (25) TLR4 rs4986790 Ex4+636A>G AA 112 (100) 385 (99) GA 2 (1) GG 0.59 0.69 0.62 0.19 0.83 0.61 0.4 0.54 0.89 0.008 0.86 0.76 0.45 1 (0) 494 (100) 3 (1) 69 (14) 418 (85) 40 (8) 461 (92) 82 (17) 254 (52) 150 (31) 459 (92) 41 (8) 155 (32) 252 (52) 82 (17) 22 (6) 347 (94) 44 (9) 235 (48) 212 (43) 7 (1) 103 (21) 386 (78) 13 (3) 111 (23) 362 (74) 173 (35) 246 (50) 77 (16) 318 (65) 155 (32) 16 (3) 48 (10) 211 (43) 234 (47) 17 (4) 158 (33) 304 (63) 373 (75) 114 (23) 13 (3) 302 (62) 165 (34) 17 (4) 234 (47) 218 (44) 48 (10) 304 (62) 166 (34) 19 (4) 83 (17) 248 (50) 170 (34) 135 (28) 232 (48) 120 (25) 182 (37) 253 (51) 58 (12) 238 (49) 195 (40) 55 (11) 21 (4) 179 (36) 296 (60) 17 (3) 130 (27) 343 (70) 138 (29) 222 (46) 122 (25) 225 (46) 217 (44) 48 (10) 497 (100) 2 (0) 416 (91) 38 (8) 2 (0) <0.0001 <0.0001 <0.0001 <0.0001 0.25 <0.0001 <0.0001 0.0002 <0.0001 <0.0001 0.0005 0.003 <0.0001 <0.0001 Immunogenetics (2007) 59:839852 845 Table 3 (continued) Genotypes Southern Chinese Northern Chinese S. vs N. Chinese P value Chinese TNF rs1800629 -487A>G AA GA 12 (11) 34 (9) GG 101 (89) 353 (91) TNF rs1799724 -1036C>T CC 80 (73) 288 (74) TC 28 (25) 93 (24) TT 2 (2) 6 (2) VCAM1 rs3176879 Ex9+149G>A AA 78 (69) 264 (68) GA 31 (27) 107 (28) GG 5 (4) 15 (4) 0.55 0.93 0.98 46 (9) 454 (91) 368 (74) 121 (24) 8 (2) 342 (69) 138 (28) 19 (4) Caucasians Chinese vs. Caucasian P value 15 (3) 121 (25) 353 (72) 379 (79) 98 (20) 5 (1) 460 (95) 23 (5) 1 (0) <0.0001 0.22 <0.0001 the chimpanzee sequence (NW_107077) was obtained from GenBank (http://www.ncbi.nlm.nih.gov/entrez/). Genotyping of DNA samples from all four studies was carried out at the National Cancer Institute Core Genotyp- ing Facility (CGF, Advanced Technology Corporation, Gaithersburg, MD) by endpoint-read TaqMan assays on an ABI 7900HT sequence detection system as described on the SNP500 website (Packer et al. 2006b). For the primary analyses, genotype frequencies were analyzed only for SNPs genotyped in the Caucasian population and at least one of the Chinese studies. A 2 test was used to test the comparisons between groups. A Pearson 2 test with 1 df was used to test for Hardy Weinberg equilibrium (HWE) based on observed genotype frequencies. Genetic diversity at each SNP was measured using two different measures: FST and d. FST measures the reduction in pooled heterozygosity due to population subdivision and was calculated using the formula, FST ,HT HS HT where HT is the expected heterozygosity in the total population, and HS is the observed heterozygosity (Lewontin and Krakauer 1973). All FST values less than 0 were set equal to 0. The second measure, d, measures the genetic divergence between subpophulations and was cailculated using the formula, d 1 p1p21=2q1q21=2 , where p1 and p2 are the frequencies for the first allele of a biallelic SNP in the two subpopulations, respectively, and q1 and q2 are the frequencies for the second allele in the two subpopulations, respectively (Nei and Chakravarti 1977). Further analysis restricted to females yield simi- lar results. We present data here that include all study subjects. For the IL4 follow-up analysis, haplotypes were estimat- ed separately for each of the 52 groups using PHASE (Stephens et al. 2001). The phylogeny of the common observed haplotypes and the chimpanzee sequence was reconstructed using MEGA3.1 (Kumar et al. 2004). Results A total of 45 SNPs in 30 genes that have been related to immune responses were analyzed (Table 1) according to the genotype frequency distribution and genetic diversity across three populations. Table 2 shows the distribution of characteristics for all study subjects from the three populations: northern Chinese (Han), southern Chinese (Han), and Caucasians. Han Chinese have traditionally been geographically divided by the Yangtze River into two parts, northern Han Chinese and southern Han Chinese. In our study, there were more females in the northern Chinese group compared to the southern Chinese group because of the study designs from which these subjects came. There was no correlation between sex and genotype frequency in the Chinese population except LTA IVS1+90G>A (P=0.01). All loci were nominally in HW equilibrium, except for two SNPs (IL4R rs2107356 -28120T>C and LTA rs909253 IVS1+90G>A) for the northern Chinese population and two SNPs (IL4 rs2243250 -588C>T and rs2070874 Ex1168C>T) for the Caucasian population showed small departures from HardyWeinberg equilibrium (HWE) (0.05>p>0.01). Quality control data were rechecked, and the accuracy was confirmed for each assay that was not in HWE. The concordance rates for the QC samples for all SNPs in the three studies are >99%. Therefore, it is likely that these deviations from HardyWeinberg proportions occurred by chance. As expected, the genotype frequencies between northern and southern Chinese for most of the SNPs were similar, with the exception of IL4 rs2243290 IVS39A>C and LTA rs909253 IVS1+90G>A (Table 3), which are probably due to chance (p values were between 0.05 and 0.01). Therefore, we combined the northern and southern Chinese subjects together. The genotype frequencies between the Chinese and Caucasians for the majority of the SNPs were 846 Table 4 SNPs genotyped in the control samples from the Xuan Wei, Tianjin, and Connecticut population-based studies and estimates of genetic diversity, Chinese vs Caucasian, sorted by FST high to low Gene IL4 IL4 IL4 IL4 CSF2 IL6 IL10 IL5 IL10 IL10 CX3CR1 CSF2 IL1RN IL1A VCAM1 IFNGR2 IL1B TLR4 IL10 TGFB1 TNF IL1A IL4R CCR5 IL10 ICAM1 IL8RB IL12A IL2 IL12B IL15RA IL13 IL8 IL13 MIF IL8RA IL13 IFNG LTA TNF CXCL12 IL8 IL8 FCGR2A IL4 dbSNP IDs Rs2243290 rs2243268 rs2243250 rs2070874 rs1469149 rs1800795 rs1800871 rs2069812 rs3024491 rs3024496 rs3732379 rs25882 rs454078 rs1800587 rs3176879 rs9808753 rs1143627 rs4986790 rs1800890 rs1800469 rs1800629 rs17561 rs2107356 rs2734648 rs3024509 rs5491 rs1126580 rs568408 rs2069762 rs3212227 rs2296135 rs1800925 rs2227306 rs20541 rs755622 rs2234671 rs1295686 rs1861494 rs909253 rs1799724 rs1801157 rs2227307 rs4073 rs1801274 rs2243248 Immunogenetics (2007) 59:839852 Location and notes IVS3-9A>C IVS2-1443A>C -588C>T, aka -524 Ex1168C>T, 5UTR -674A>C -236C>G, aka -174 -853C>T, aka -819 -745C>T IVS1-286G>T Ex5+210C>T, 3UTR V249I I117T IVS6+59A>T, aka A9589T Ex1+12G>A, aka -889, 5UTR K644K Q64R -580C>T, aka -31 D299G -3584A>T -1346C>T, aka -509 -487A>G, aka -308 A114S -28120T>C IVS1+151G>T IVS3-58C>T K56M Ex3-1010G>A, 3UTR Ex7+277A>G, 3UTR; aka 8685G>A IVS1-100G>T Ex8+159A>C, 3UTR Ex8-361A>C, 3UTR -1069C>T IVS1-204C>T Q144R -269G>C, aka -173 S276T IVS324T>C IVS3+284G>A IVS1+90G>A, aka NcoI, aka A252G -1,036C>T, aka -857 Ex4+535C>T, 3UTR IVS1+230G>T -351A>T, aka -251 H165R -1,098G>T d 0.231 0.232 0.224 0.207 0.131 0.147 0.097 0.091 0.126 0.129 0.075 0.080 0.024 0.034 0.037 0.069 0.006 0.015 0.094 0.014 0.018 0.034 0.001 0.011 0.031 0.032 0.026 0.001 0.001 0.028 0.005 0.004 0.001 0.008 0.002 0.006 0.007 0.002 0.002 0.001 0.001 0.001 0.000 0.000 0.000 FST 0.414 0.410 0.404 0.399 0.225 0.203 0.187 0.182 0.166 0.164 0.160 0.137 0.118 0.108 0.108 0.094 0.076 0.069 0.068 0.060 0.059 0.058 0.044 0.043 0.042 0.036 0.034 0.032 0.028 0.027 0.023 0.006 0.005 0.005 0.003 0.002 0 0 0 0 0 0 0 0 0 statistically different (P<0.01) (Table 3). For several SNPs, the most common allele was different between the populations. For example, the C allele at IL4 IVS21443 (rs2243268) was found to be common among Chinese (79%), but uncommon among Caucasians (15%). As the southern Chinese subjects were more comparable to the Caucasian subjects in terms of age than the younger northern Chinese subjects, we compared genotype frequencies of the former directly with the Caucasian population, and the results are very similar to the comparison of the combined Chinese population and Caucasians using likelihood ratio test, adjusting for age (data not shown). However, as data were available for IL10 rs1800890 3584T>A only in the Northern Chinese population, we explored age effects in that group and among the Caucasian group. After adjusting for age, the results remained similar. As such, the striking difference in genotype frequencies (Table 3) could not have been due to the difference in age Immunogenetics (2007) 59:839852 Table 5 Common IL10 and IL4 haplotypes among the three populations 847 a Order of SNPs comprising IL10 haplotypes: rs3024496, rs3024491, rs1800872, rs1800871, rs1800896. Order of SNPs comprising IL4 haplotypes: rs2243248; rs2243250; rs2070874; rs2243268; rs2243290. b Colors identify IL4 haplotypes presented in Fig. 1. of the two groups. Also, we note that the difference in genotype frequencies for this SNP are similarly apparent across Caucasians and Pacific Rim populations in the NCI SNP500Cancer database (Hughes et al. 2005;Packer et al. 2006a). Furthermore, results were similar when the analysis was restricted to females. Estimates of genetic diversity (FST and d) are presented in Table 4. Several SNPs in IL4 showed substantial genetic differentiation (Fst>0.25 and d>0.20), and one or more SNPs in CSF2, IL6, and IL10, and CX3CR1 showed moderate genetic differentiation (0.15<FST<0.25). Table 5 shows estimated IL10 and IL4 haplotypes based on ten and five SNPs, respectively, and their frequencies in the three populations, which differed markedly between the Caucasian and Chinese groups (p<0.0001). The haplotype distribution of the five IL4 SNPs is shown graphically in the three populations (Fig. 1). We genotyped ten IL4 SNPs in the (N=1056) Human Diversity panel (HDP) samples (five in primary analysis and five additional SNPs to provide more coverage of the locus) to characterize worldwide haplotype distributions at the IL4 locus. Overall, a total of 18 haplotypes were observed at a frequency of >5% among the HDP groups. Figure 2 shows the distributions of common (>5%) haplotypes by location for the 52 HDP groups. For comparative purposes, haplotypes estimated to occur at <5% frequency were excluded from these plots; in nonAfrican groups these rare haplotypes only account for between 0 and 6% of the total for each group. As expected, the African groups exhibited more (between four and ten common haplotypes) diversity than those of European, Asian, Oceania, or Native American origin. Figure 3 shows a phylogenetic tree, based on proportion of distance (p), which was reconstructed using the 18 observed haplotypes (numbered arbitrarily) and their average frequencies in the seven geographic groups and the sequence from the chimpanzee. A high degree of variability of haplotype frequencies was observed within the major geographic regions, particularly in the African group, which has the greatest haplotype diversity and Fig. 1 Estimated haplotype distributions for 5 IL4 SNPs (see a b c Table 5 footnote for identifica- tion of haplotypes) for A N=390 individuals from Tianjin, China, B N=112 individuals from Xuan Wei County, C N=491 Caucasian individuals from Connecticut 848 Immunogenetics (2007) 59:839852 Fig. 2 IL4 haplotype distribution graphs for the 52 populations in the Human Diversity Panel (HDP). Map used with permission from Google 10 24 25 31 18 1 13 19 26 21 22 6 27 29 32 28 3 15 chimp Sequence GTTTACCGGA .G........ .G..G.A.A. A...G.A.A. .GC...A.A. ..CC..A.A. .GCC..A.AC .G.C.GA.AC .G..GGA.AC .G.CG.A.AC .G.CGGA.AC ...C.GA.AC A.CC.GA.AC A..C.GA.AC A...GGAAAC A.CC.GAAAC ..CC.GAAAC .GCC.GAAAC ..C..GA.AC African 0.15 0.04 0.02 0.02 0.03 0.01 0.02 0.04 0.03 0.04 0.18 0.02 0.01 0.06 0.01 0.12 0.16 European W. Asian C/S Asian E. Asian Oceanians N American 0.14 0.12 0.20 0.80 0.43 0.65 0.08 0.02 0.80 0.66 0.65 0.14 0.48 0.15 0.04 0.15 0.13 0.05 0.19 0.5 Fig. 3 Phylogenetic tree and average frequencies of IL4 haplotypes. Order of IL4 SNPs is as follows: rs2243247; rs2243248; rs2243250; rs2070874; rs2243251; rs2243267; rs2243268; rs2243270; rs2243289; rs2243290 Immunogenetics (2007) 59:839852 849 lower frequency of the common haplotypes as shown in Fig. 3. Most of the observed haplotypes were present in the African groups, while in non-Africans, only one to three haplotypes were observed. Although the number of observed haplotypes was consistently low, and the haplotypes, themselves, were the same among these nonAfrican groups, the frequencies of the haplotypes were remarkably different between groups from Europe and Western/Central/Southern Asia than those in Eastern Asia, Oceania, and Native Americans (Figs. 2 and 3). For example, haplotypes 10 and 3 (Fig. 3) occurred at a frequency of 80 and 14%, respectively, in Eastern Asians and at 14 and 80% in Europeans. Three of the most uniformly frequent haplotypes observed were 3, 10, and 15 (as shown in Fig. 3). Phylogenetically, haplotype 10 is distantly related haplotype to both 3 and 15, which are closely related to each other. Haplotypes 3 and 15 are also more closely related to the chimpanzee (ancestral) sequence. In Fig. 3, the 589 putatively functional SNP is outlined in red. While the chimpanzee and haplotypes 3 and 15 contain the C allele, haplotype 10 contains the T allele, which has been associated with increased levels of IL4. It is interesting to note that in the two populations from the Oceanic region, a novel haplotype (no. 1, Fig. 3) is observed that is unique to this region. Discussion We identified a subset of cytokine SNP genotypes that varied substantially between the Caucasians and Chinese populations. SNPs in the IL4 gene showed the greatest genetic differentiation and SNPs in the CSF2, IL6, and IL10, and CX3CR1 genes showed moderate differentiation. A previous report found evidence of genetic diversity for several of these same SNPs across a total of 102 DNA samples from a nonrandom sample of subjects in four ethnic groups (i.e., Caucasian; African-American; Pacific Region; Hispanic Caucasians) using the NCI SNP500 database (Hughes et al. 2005). Other reports have compared SNPs in one or more of the cytokine genes we studied between Asians and Caucasians (Hoffmann et al. 2002; Marron et al. 1997; Rockman et al. 2003). However, the study populations were smaller than ours. We have extended observations from these previous reports in a relatively large series of almost 1,000 subjects, including two groups that represent a sample of their respective populations--Han Chinese from Southern and Northern China and Caucasians in the United States. Our findings are consistent with previous reports on genotype frequencies of the same IL4 SNP -588C>T (rs2243250) in various populations, although those studies were substantially smaller than ours, and in many instances, did not define the extent to which the findings could be applied to the population at large. For example, the TT genotype frequency has been reported to be 1.8% in Caucasians in the UK (Heward et al. 2001), 2% in Caucasians in the US (Wang et al. 2006), 6% in Australians (Annells et al. 2004), 9% in Egyptians (Hegab et al. 2004), 47% in Japanese (Hegab et al. 2004), 49% in Filipinos (Bugawan et al. 2003), 63% in Chinese (Yang et al. 2005), and about 70% in Taiwan Chinese (Tsai et al. 2005; Wu et al. 2003). The pattern of distribution of common haplotypes across IL4 is striking in relation to geography. In Fig. 2, there is a clear divide between East Asia and Europe and Central Asia with respect to the frequency distribution of common haplotypes, suggesting that local selective pressure or assertive mating could be more recent for geographically distinct regions. It is also apparent that the haplotype frequencies for IL4 display the `yingyang' phenomenon, namely, two haplotypes with near-mirror frequencies (Zhang et al. 2003). For IL4, a gene critical in immune regulation, it is plausible that recent natural selection could be driven by one or more discrete environmental challenges, such as infection, which could be unique to either side of this "genetic divide', or perhaps both. Further studies are required to determine whether population splitting with maintenance of lineage by selection or genetic drift is responsible for this finding. The IL4 gene mediates a number of key immune pathways. It plays an important role in the proliferation and differentiation of T cells, inhibits Th1-induced signals, influences Th1/Th2 balance, provokes B cells to undergo immunoglobulin type-switching, participates in IgE synthesis (Finkelman et al. 1986), and down-regulates expression of CCR5 (major coreceptors for HIV). In vitro data have shown that promoter SNPs in IL4 -588C>T have increased reporter gene expression (Nakashima et al. 2002). Association studies of diseases suggest that SNPs in the IL4 gene may now be associated with severity of infection in diseases that can be suitably supported or treated, such as respiratory syncytial virus (RSV) in young children, asthma, atopy, atopic dermatitis, fungal infection with Candida albicans in leukemia patients, inflammatory bowel disease, and altered HIV survivorship in an HIV + cohort (Beghe et al. 2003; Burchard et al. 1999; Choi et al. 2002, 2003; Hoebee et al. 2003; Kawashima et al. 1998; Noguchi et al. 2001; Pawlik et al. 2005; Rockman et al. 2003; Zhu et al. 2000). In addition, we have recently reported that SNPs in IL4 were associated with increased risk of nonHodgkin lymphoma (NHL) or for specific NHL subtypes (Lan et al. 2006; Purdue et al. 2006). It is noteworthy that SNP genotype frequencies in three genes that exhibited moderate to substantial variation between our Chinese and Caucasian populations play important roles in the T helper 2 (Th2) pathway (i.e., IL4, IL6, and IL10). Th2 850 Immunogenetics (2007) 59:839852 lymphocytes and other related cells produce IL-4, IL-6, and IL-10 that control humoral immunity by up-regulating antibody production to protect against extracellular pathogens. These cytokines play an important role in immunoglobulin production, lymphoid development, and balance immune function. Studies have reported that SNPs in these cytokines may be associated with a wide variety of diseases, including NHL (Akira and Kishimoto 1992; Brouet and Levy 1991; Deng et al. 2002; Gauldie et al. 1992; Lan et al. 2006; Powrie and Coffman 1993a,b; Schuitemaker 1994; Swain 1993; Tepper 1993). A large pooled analysis and a recent report found that the IL10 -3584A variant was associated with an increased risk of NHL, particularly diffuse large B-cell lymphoma, among Caucasians (Purdue et al. 2006; Rothman et al. 2006). Interestingly, Chinese have a lower incidence of NHL and the A allele was found to be less in frequency in Chinese compared to Caucasians in our data (3 vs 33%, respectively, p<0.0001). In conclusion, we have found that SNPs in several genes that play important roles in immune function vary substantially in genotype frequency across Chinese and Caucasians populations. It is interesting that SNPs with the highest FST values were in genes that regulate the Th2 pathway, which have pleiotropic functions including response to infectious agents and modulation of the inflammatory process. 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