Hum Genet (2007) 121:35–42 DOI 10.1007/s00439-006-0295-x

ORIGINAL INVESTIGATION

The (C-C-motif) receptor 3 (CCR3) is linked and associated with age at menarche in Caucasian females

Fang Yang · Dong-hai Xiong · Yan Guo · Hui Shen · Peng Xiao · Feng Zhang · Hui Jiang · Robert R. Recker · Hong-wen Deng

Received: 8 July 2006 / Accepted: 6 November 2006 / Published online: 5 December 2006 © Springer-Verlag 2006

Abstract Chemokine (C-C-motif) receptor 3 ciations between CCR3 polymorphisms and AAM in a (CCR3), playing an important role in endometrium selected random sample of daughters using ANOVA related metabolic pathways, may inXuence the onset of (analysis of variance). We identiWed two haplotype menarche. To test linkage and/or association between blocks. Only block two showed signiWcant results. CCR3 polymorphisms with the variation of age at men- After correction for multiple testing, signiWcant total arche (AAM) in Caucasian females, we recruited a associations of SNP7, SNP9 with AAM were detected sample of 1,048 females from 354 Caucasian nuclear (P = 0.009 and 0.006, respectively). We also detected families and genotyped 16 SNPs spanning the entire signiWcant within-family association of SNP9 CCR3 gene. Linkage disequilibrium and haplotype (P = 0.01). SNP14 was linked to AAM (P = 0.02) at the blocks were inferred by Haploview. Both single-SNP nominal level. In addition, there was evidence of sig- markers and haplotypes were tested for linkage and/or niWcant total association and nominal signiWcant link- association with AAM using QTDT (quantitative age (P = 0.008 and 0.03, respectively) with AAM for transmission disequilibrium test). We also tested asso- the haplotype AGA reconstructed by SNP7, SNP9 and SNP13. ANOVA conWrmed the results by QTDT. For the Wrst time we reported that CCR3 is linked and Fang Yang and Dong-hai Xiong had contributed equally to this associated with AAM variation in Caucasian women. work. However, further studies are necessary to substantiate F. Yang · H. Jiang · H.-w. Deng (&) our conclusions. Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, People’s Republic of China Introduction e-mail: [email protected]

Y. Guo · F. Zhang · H.-w. Deng Menarche is the hallmark maturational event in a The Key Laboratory of Biomedical Information Engineering female’s life. Early menarche is a risk factor for breast of Ministry of Education and Institute of Molecular Genetics, cancer, endometrial cancer (Rees 1995) and cardiovas- School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, People’s Republic of China cular disease (Remsberg et al. 2005). Delayed menar- che is associated with irregular menstrual cycles (Anai F. Yang · D.-h. Xiong · H. Shen · P. Xiao · F. Zhang · et al. 2001; Kjaer et al. 1992) and increases the risk of H. Jiang · R. R. Recker osteoporosis (Anai et al. 2001; Ulrich et al. 1995). Osteoporosis Research Center and Department of Biomedical Sciences, Therefore, from a clinical point of view, it is of interest Creighton University, Omaha, NE 68131, USA to identify factors that may inXuence the variation of age at menarche (AAM). H.-w. Deng Age at menarche is a complex trait determined by Department of Orthopedic Surgery, School of Medicine, University of Missouri-Kansas City, 2411 Holmes Street, multiple environmental and genetic factors (Chie et al. Kansas City, MO 64108, USA 1997; Kaprio et al. 1995; Meyer et al. 1991; Treloar and 123 36 Hum Genet (2007) 121:35–42

Martin 1990). Previous investigations based on twin Signed informed-consent documents were obtained and family studies demonstrated that genetic factors from all participants before entering the study. Ini- can explain about 53–74% of the variation of AAM tially, all of the 1,873 participants from 405 nuclear (Chie et al. 1997; Kaprio et al. 1995; Sharma 2002). families were US Caucasians of European origin Linkage and association studies have suggested either recruited from Omaha and its surrounding areas for quantitative trait loci (QTLs) or candidate bone mineral density (BMD) research. For menarche underlying the variation of AAM, such as genomic study, we selected families that contain at least two region of 22q13 (Guo et al. 2006) and the genes like informative female subjects (¸1 daughters) with AAM cytochrome P450, subfamily XVII (CYP17) (Gorai data. At Wrst, 50 families having only male oVsprings et al. 2003; Lai et al. 2001), estrogen receptor  (ER-) and 1 family without enough AAM data for daughters (Long et al. 2005; Stavrou et al. 2002) and sex hor- were excluded. To select “healthy” subjects for AAM mone-binding globulin (SHBG) (Xita et al. 2005). study from the remained 354 families, females with However, the genetic studies in this Weld are still lack- diseases (such as gynecopathia, eating disease, and ing and the results have been inconsistent. kidney disease) relevant to AAM before menarche During the immediate premenstrual phase, there is were excluded. At last, 1,048 female subjects from 354 an inXux of macrophages, neutrophils, and eosinophils nuclear families were studied, aging from 19 to into the endometrium. Circulating leukocytes into 85 years old. endometrium tissues is a complex process requiring the production of by leukocytes. Of these AAM data chemokines, eotaxin, belonging to the CC group of chemokines and acting through its receptor CCR3, is For each study subject, a detailed medical history, the most selective for eosinophils. Zhang et al. (2000) including menstrual history was recorded by nurse- identiWed that eotaxin and CCR3 were strongly administered questionnaire. AAM was collected using expressed by human eosinophils and endometrial epi- a retrospective method. The correlation between the thelials using immunohistochemical analyses. It has self-recalled menarche age and observed menarche age been conWrmed that eotaxin acted as a paracrine is signiWcantly high because menarche is an important growth factor and regulates eosinophils into endome- change both physiologically and psychologically in a trium through CCR3 (Zhang et al. 2000). Eosinophils female’s life (Kirchengast et al. 1998). AAM was calcu- are likely to be critical for the focal inXammatory endo- lated as the date of menarche following the onset of metrial tissue breakdown, which characterizes men- menses minus the date of birth (in years rounded to the struation (Jones et al. 2004; Salamonsen and Lathbury tenth decimal). After excluding three outliers whose 2000). As menarche is the Wrst natural endometrium AAM were 18 year or older (diagnosed as primary destruction in a women’s life, it is possible that CCR3 amenorrhea), our AAM data followed normal distri- may inXuence the onset of menarche given the role of bution as veriWed by the Kolmogorov–Smirnov test CCR3 in endometrium related metabolic pathways. implemented in the software Minitab (Minitab Inc., This study represents our eVort to test such hypothesis State College, PA, USA). AAM of the Wnal sample and is the Wrst association study aiming at investigating ranged from 8.5 to 17.0 years with a mean of 13.0 the relationship between CCR3 and AAM. We investi- (SD = 1.4). As environmental factors, such as date of gated the LD (linkage disequilibrium) patterns and birth, may aVect AAM, we performed correlation anal- haplotype structures using high density SNPs of CCR3, ysis between birth year and AAM but found no signiW- and tested for linkage and/or association with AAM cant association (P = 0.874) in the present sample. So variation by quantitative transmission disequilibrium we did not include birth year as a covariate in the sub- test (QTDT) in a large sample of Caucasian nuclear sequent association analyses. families. SNP selection and genotyping

Subjects and methods A total of 16 SNPs in and around CCR3 gene were selected on the basis of the following criteria: (1) vali- Subjects dation status, especially in Caucasians, (2) an average density of 1 SNP per 3 kb, (3) degree of heterozygosity, This study was approved by the Creighton University i.e., minor allele frequencies (MAF) >0.05, (4) func- Institutional Review Board. The design and sampling tional relevance and importance, (5) reported to procedures were published before (Xiong et al. 2005). dbSNP by various source. Genomic DNA was 123 Hum Genet (2007) 121:35–42 37 extracted from whole blood using a commercial isola- used to test each SNP and haplotype with estimated tion (Gentra Systems, Minneapolis, MN, USA) fol- frequencies greater than 5% for linkage and associa- lowing the procedure detailed in the kit. DNA tion with AAM variation. It was based on the vari- concentration was assessed by a DU530 UV/Vis Spec- ance component framework and can test population trophotometer (Beckman Coulter, Inc, Fullerton, CA, stratiWcation, total association, within-family associa- USA). All the subjects were genotyped, yield a large tion, linkage and linkage while modeling association set of genotype data that are further subject to Mende- simultaneously. We adopted the orthogonal model lian inheritance checking, allele frequency estimation (Abecasis et al. 2000), which decomposes the total  and haplotype reconstruction. About 16 SNPs were association into orthogonal between ( b) and within-  successfully genotyped using the high-throughput family ( w) components. The between-family compo- BeadArray SNP genotyping technology of Illumina Inc nent is sensitive to population admixture, while the (San Diego, CA, USA). The average rate of missing within-family component is signiWcant only in the genotype data was reported by Illumina to be »0.05%. presence of LD and robust to population stratiWca- The average genotyping error rate estimated through tion/admixture. If signiWcant associations were blind duplicating was reported to be less than »0.01%. observed, the phenotypic variation due to the The 16 SNPs were spaced »2.7 kb apart on average detected marker is calculated as 2p(1¡p)a2, where p and covered the full transcript length of the CCR3 is the allele frequency of the marker and a is the esti- gene. mated additive variance. Population stratiWcation is   tested according to whether b = w (Fulker et al. Statistical analysis 1999). If there is no population stratiWcation   ( b = w), the test result of total association should be Using PedCheck (O’Connell and Weeks), we more powerful (Abecasis et al. 2000). checked the Mendelian consistency of SNP genotype Linkage tests are based on the standard variance data and removed any inconsistent genotypes. Then component method and identity by decent (IBD) shar- the error checking option embedded in Merlin ing among relatives. The program SimWalk2 (http:// (Abecasis et al. 2002) was run to identify and disre- www.genetics.ucla.edu/software/simwalk2) was used to gard the genotypes Xanking excessive recombinants, calculate IBD probabilities. A test for linkage while thus further reduced genotyping errors. Allele fre- modeling association (Fulker et al. 1999) is also imple- quencies for each SNP were calculated by allele mented in QTDT to evaluate whether a study marker counting, and the Hardy-Weinberg equilibrium is a functional variant. If the signiWcant linkage is still (HWE) was tested using the PEDSTATS procedure detected after modeling association, we can conclude embedded in Merlin. Linkage disequilibrium block that the candidate marker is only in linkage disequilib- structure was examined by the program Haploview rium with the lurking causal variant instead of being (Barrett et al. 2005) using 703 unrelated parents. The the causal one itself. |DЈ| values for all pairs of SNPs were calculated and Since multiple markers were analyzed, a correction the haplotype blocks were estimated using the conW- for multiple testing is required. The commonly used dence-interval method (Gabriel et al. 2002). SNPs method is Bonferroni correction. However, the Bon- with low MAF may inXate estimates of |DЈ| and the ferroni correction seems to be too conservative and use of conWdence-bound estimates for |DЈ| reduces potentially result in loss of statistical power (Nyholt this bias. We used the default settings which invoked 2001). This is because that some statistical tests here a one-sided upper 95% conWdence bound of are highly correlated as some SNPs in the CCR3 gene |DЈ| > 0.98 and a lower bound of |DЈ| > 0.7 to deWne are in signiWcant strong LD. Therefore, Monte-Carlo SNP pairs in strong LD. When at least 95% of SNP permutation test (McIntyre et al. 2000) were per- pairs in a region meet these criteria for strong LD, a formed 1,000 times to establish an empirical threshold, block is identiWed. Haplotype tag SNPs (htSNPs) which was P · 0.01 for an individual test to achieve a were selected by Haploview on a block-by-block global signiWcance level of 0.05 for our analyses in the basis. Haplotypes deWned by the tagging SNPs within present study. each block of CCR3 gene for all of the studied sub- One daughter from each of the 354 nuclear families jects were inferred by PedPhase V2.0 (http://www. was randomly selected for population-based associa- cs.ucr.edu/»jili/haplotyping.html). tion analysis, which was performed by SPSS 11.5 (Lan- The QTDT software (http://www.sph.umich.edu/ guage systems Corp, Chicago). The Wnal random csg/abecasis/QTDT/), a powerful family based test for sample included 351 daughters after excluding 3 nuclear families of any size (Abecasis et al. 2000), was daughters without menarche data. 123 38 Hum Genet (2007) 121:35–42

Results sense polymorphism in the dbSNP for CCR3. The MAFs of these 16 SNPs ranged from 0.07 to 0.45. All Allele frequencies, LD and haplotype reconstruction the SNPs were in HWE (P >0.01). We identiWed two blocks with high LD, with the sizes of 10 and 31 kb, The information of all the CCR3 SNPs was summa- respectively. Block one ranged from 5Ј UTR (untrans- rized in Table 1. There is no potential functional mis- lated region) to intron1 with SNP1 and SNP2 selected as htSNPs. Block 2 extended from intron1 to 3Ј UTR Table 1 SNP marker information with SNP7, SNP9 and SNP13 selected as htSNPs SNP Markera Minor allele Rolec Allels Positionb (Fig. 1). Therefore, four block one haplotypes and frequence eight block two haplotypes were reconstructed accord- ingly with their frequencies presented in Table 2. 1 rs13067058 0.0738(A) 5Ј UTR A/G 46248770 2 rs1388604 0.3654(T) 5Ј UTR A/T 46251882 3 rs9842716 0.4581(A) 5Ј UTR A/G 46257178 QTDT analyses 4 rs9853223 0.4576(A) Intron1 A/G 46259097 5 rs13073976 0.0719(A) Intron1 A/G 46261667 Table 3 summarizes the linkage and association results 6 rs13068209 0.3251(A) Intron1 A/G 46269961 7 rs6441948 0.4434(A) Intron1 A/G 46270718 of CCR3 gene with AAM in nuclear families by 8 rs9811301 0.324(A) Intron1 A/C 46275552 QTDT. As block one polymorphisms showed no sig- 9 rs3091309 0.1907(A) Intron1 A/G 46278188 niWcant results, here we only included the results of 10 rs1491962 0.4447(G) Intron2 A/G 46279630 block two polymorphisms. We did not Wnd any signiW- 11 rs17217831 0.0729(A) Intron2 A/C 46280445 W 12 rs4987053 0.0746(G) Exon3 A/G 46281704 cant evidence of population strati cation for either 13 rs3091312 0.2492(T) 3Ј UTR A/T 46283476 single-SNP markers or haplotypes. This Wnding might 14 rs1388603 0.4452(A) 3Ј UTR A/G 46286070 rule out the confounding eVect of population stratiWca- Ј 15 rs1027241 0.4455(A) 3 UTR A/G 46287543 tion on the tests of total association. For single-SNP 16 rs6773018 0.4453(A) 3Ј UTR A/G 46293055 marker analyses, after correcting for multiple tests, a SNP ID in the dbSNP (http://www.ncbi.nlm.nih.gov/SNP) we detected signiWcant total associations for SNP7 b position in dbSNP (http://www.ncbi.nlm.nih.gov/ (P = 0.009) and SNP9 (P = 0.006) and signiWcant SNP) within-family association for SNP9 (P = 0.01). The con- c Only one exonic SNP (rs4987053) is included; two other non- tributions of SNP7, SNP9 to AAM variation were 1.45 synonymous SNPs (rs4987125 and rs5742906) are listed in the db- SNP but they are rare (<1%) and 1.93%, respectively, calculated by total association test. At the nominal signiWcant threshold of P · 0.05,

Fig. 1 Linkage disequilib- rium pattern of CCR3 gene. Block 1 ranged from SNP1 to SNP4, with size of »10 kb, block 2 ranged from SNP5 to SNP16, with size of »31 kb

123 Hum Genet (2007) 121:35–42 39

Table 2 Haplotype information signiWcant linkage signal (P = 0.02), suggesting that Haplotype Frequency SNP14 could not be a causal variant underlying AAM. Four major haplotypes with frequencies above 5% Block 1a (AAA, AGA, GGA and GGT) in block two were ana- AA 0.565 lyzed by QTDT. We detected further evidence of nom- AT 0.356 W GA 0.078 inal linkage (P = 0.04) and signi cant total association GT 0.001 (P = 0.008) for haplotype AGA. The contribution of Block 2b haplotype AGA to the variation of AAM was 2.01%. AAA 0.184 Linkage signal was still nominal signiWcant after mod- AAT <0.001 AGA 0.261 eling association (P = 0.03), implying that it may only AGT 0.001 be a in linkage disequilibrium with AAM varia- GAA <0.001 tion. However, we did not Wnd any evidence of within- GAT <0.001 family association for the four haplotypes. On the GGA 0.306 GGT 0.248 whole, the total associations with AAM variation were consistent between haplotype AGA and its component a Haplotypes were reconstructed with SNP1 and SNP2 alleles of single-SNPs. In our sample, females carrying b Haplotypes were reconstructed with SNP7, SNP9 and SNP13 haplotype AGA (AAM 13.20 § 1.55) were, on aver- age, 4 months later (P = 0.01) in terms of the onset of signiWcant total association for SNP10 (P = 0.03) and menarche compared with the non-carriers (AAM within-family associations for SNP7 (P = 0.04) and 12.84 § 1.38). SNP10 (P = 0.02) were also observed. Within-family associations were in well consistent with total associa- Population association analyses tions for these polymorphisms. Interestingly, for SNP13, we found nominal signiWcant within-family We further investigated the associations of CCR3 poly- association (P = 0.03), but no signiWcant signal of total morphisms with AAM variation in a random female association due to borderline signiWcant population sample by population-based association analysis. The stratiWcation (P = 0.09). In addition, the linkage signal signiWcant single-SNP markers were SNP6, SNP7, to AAM was nominal signiWcant for SNP14 (P =0.02). SNP9, SNP10, SNP13 and SNP15 (P = 0.04, 0.008, After modeling association, there was still nominal 0.0008, 0.005, 0.02 and 0.01, respectively), with the

Table 3 QTDT analyses for the linkage and association between block 2 polymorphisms of CCR3 and age at menarche (AAM) variation SNP Marker StratiWcation Within-family Total Linkage Linkage modeling association association association

5 rs13073976 – – – – – 6 rs13068209 – 0.07 – – – 7 rs6441948 – 0.04* 0.009** – – 8 rs9811301 – 0.07 – – – 9 rs3091309 – 0.01** 0.006** – – 10 rs1491962 – 0.02* 0.03* – – 11 rs17217831 – – – – – 12 rs4987053 – – – – – 13 rs3091312 0.09 0.03* – – – 14 rs1388603 – – 0.08 0.02* 0.02* 15 rs1027241 – 0.09 0.06 – – 16 rs6773018 – 0.09 0.06 – – Block 2 Haplotype 0.04* AAA – – – 0.03* AGA 0.08 0.09 0.008** 0.03* GGA – – – 0.05* GGT – – – 0.03* Data not shown for block one polymorphisms, for which there is no signiWcant evidence of either linkage or association – P >0.10 *SigniWcant results at the nominal threshold P · 0.05 **Global signiWcant results at the empirical threshold P ·0.01 after 1,000 times Monte Carlo permutation

123 40 Hum Genet (2007) 121:35–42 contributions to AAM variation in our sample of 1.27, carriers. Our population-based analyses conWrmed the 1.98, 3.46, 2.23, 1.50 and 1.67%, respectively, as deter- family based analysis as well. In addition, the signiW- mined by the ANOVA r2 values (Table 4). We also cant within-family associations were found for SNP9. observed a signiWcant association with AAM variation Taken together, our results strongly suggested that for the haplotype AGA in block two (P = 0.001), which CCR3 polymorphisms may inXuence AAM variation could explain about 3.04% AAM variation in the pop- in Caucasian women. ulation (Table 4). These Wndings supported our QTDT It is not unexpected to detect the associations results. between CCR3 gene polymorphisms with the AAM variation. In endometrium, leukocytes, especially eosinophils rise dramatically before the focal inXam- Discussion matory endometrial destruction. Leoukocytes produce a series of chemokins and cytokins including CCR3 Previous data have established the genetic control of that in concert result in focal production and activation AAM variation (Chie et al. 1997; Guo et al. 2006; of matrix metalloproteinases by endometrial cells and Kaprio et al. 1995; Long et al. 2005; Meyer et al. 1991; the subsequent breakdown of tissue characterizing Treloar and Martin 1990). In recent years, much eVort menstruation (Salamonsen and Lathbury 2000). Other has been made to Wnd and conWrm genes or genomic chemokins, such as MCP-3, and MCP-4 also bind to regions underlying AAM variation. Motivated by the CCR3 and are involved in the regulation of endome- important role of CCR3 gene in the normal function of trial cell function (Zhang et al. 2000). All those molec- endometrium, we tested linkage and/or association ular and cell studies suggested that CCR3 play an between CCR3 and AAM variation in a large Cauca- important role in menstruation (Jones et al. 2004; Sal- sian sample of 354 nuclear families. The family based amonsen and Lathbury 2000). analysis, QTDT can directly test LD between a quanti- Furthermore, we previously reported the signiWcant tative trait and a marker locus and is robust against genetic correlation between AAM and BMD in Cauca- population stratiWcation. It is a powerful tool in testing sians (Guo et al. 2005). We also detected a signiWcant linkage and association of candidate genes with com- genetic correlation between AAM and covariates- plex traits (Allison 1997). To our best knowledge, this adjusted (age, weight, menopause status) spine BMD is the Wrst family based linkage and association study (r = ¡0.1462, P < 0.001) in the present study, using the between CCR3 gene and AAM. same analysis method as in our previous study (Guo A recent genome-wide scan for AAM by our group et al. 2005). Other studies demonstrated that CCR3 (Guo et al. 2006) also revealed certain linkage evi- polymorphisms were associated with bone resorption dence to AAM variation in the CCR3 harboring region and the expression of CCR3 gene was up-regulated in in Caucasian women (LOD = 0.84, P = 0.024, in subjects with low BMD (Day et al. 2004; Graves et al. another set of pedigrees that are diVerent from pedi- 1999; Lisignoli et al. 2002; Liu et al. 2005; Murdoch and grees used in this study, but sampled from the same US Finn 2000). Together, it may be suggested that CCR3 Caucasion population). In our study, signiWcant total gene has pleiotropic eVects on both AAM and BMD, associations were found for SNP7, SNP9 and the hap- which are two closely correlated phenotypes (Kroger lotype AGA reconstructed by the htSNPs—SNP7, et al. 1993; Stoll 1998; Theintz et al. 1992; Vihko and SNP9 and SNP13 in block two. It was shown that Apter 1984). females carrying haplotype AGA were 4 months later In summary, our study Wrstly provided evidence for with respect to the onset of menarche than the non- the linkage and association between CCR3 gene poly- morphisms and AAM in Caucasian females. These Table 4 Population association analyses for CCR3 gene poly- results should be valuable in terms of initiating the fol- morphisms with AAM variation using randomly selected daugh- low-up research aiming at replicating our Wndings and ters (including only the polymorphisms with signiWcant results) identifying the associated causal functional variants Polymorphisms ANOVA P value r2 (%) inXuencing AAM variation. Our results, though, are limited within Caucasian women. So, the validity of SNP6 0.04 1.27 them in other ethnic groups awaits further investiga- SNP7 0.008 1.98 SNP9 0.0008 3.46 tion. Eventually, unraveling the hidden mechanism SNP10 0.005 2.23 driving the linkage and association observed by us will SNP13 0.02 1.50 deWnitely contribute to the understanding of the SNP15 0.01 1.67 genetic control of AAM variation that is highly corre- Haplotype AGA 0.001 3.04 lated with the bone health of women. 123 Hum Genet (2007) 121:35–42 41

Acknowledgments Investigators of this work were partially Kaprio J, Rimpela A, Winter T, Viken RJ, Rimpela M, Rose RJ supported by grants from NIH (R01 AR050496, K01 AR02170- (1995) Common genetic inXuences on BMI and age at men- 01, R01 AR45349-01, and R01 GM60402-01A1) and an LB595 arche. Hum Biol 67:739–753 grant from the State of Nebraska. The study also beneWted from Kirchengast S, Gruber D, Sator M, Huber J (1998) Impact of the grants from National Science Foundation of China, Huo Ying age at menarche on adult body composition in healthy pre- Dong Education Foundation, HuNan Province, Xi’an Jiaotong and postmenopausal women. Am J Phys Anthropol 105:9–20 University, and the Ministry of Education of China. Kjaer K, Hagen C, Sando SH, Eshoj O (1992) Epidemiology of menarche and menstrual disturbances in an unselected group of women with insulin-dependent diabetes mellitus compared to controls. 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