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Genome-wide Association and Follow-Up Replication Studies Identified ADAMTS18 and TGFBR3 as Bone Mass Candidate Genes in Different Ethnic Groups

2009; Elsevier BV; Volume: 84; Issue: 3 Linguagem: Inglês

10.1016/j.ajhg.2009.01.025

ISSN

1537-6605

Autores

Donghai Xiong, Xiaogang Liu, Yan-Fang Guo, Lijun Tan, Liang Wang, Baoyong Sha, Zihui Tang, Feng Pan, Tie‐Lin Yang, Xiang‐Ding Chen, Shu‐Feng Lei, Laura M Yerges, Xue-Zen Zhu, Victor Wheeler, Alan L. Patrick, Clareann H. Bunker, Yan Guo, Han Yan, Yu‐Fang Pei, Yin-Pin Zhang, Shawn Levy, Christopher J. Papasian, Peng Xiao, Yunxia Wang Lundberg, Robert R. Recker, Yaozhong Liu, Yongjun Liu, Joseph M. Zmuda, Hong‐Wen Deng,

Tópico(s)

Genomics and Rare Diseases

Resumo

To identify and validate genes associated with bone mineral density (BMD), which is a prominent osteoporosis risk factor, we tested 379,319 SNPs in 1000 unrelated white U.S. subjects for associations with BMD. For replication, we genotyped the most significant SNPs in 593 white U.S. families (1972 subjects), a Chinese hip fracture (HF) sample (350 cases, 350 controls), a Chinese BMD sample (2955 subjects), and a Tobago cohort of African ancestry (908 males). Publicly available Framingham genome-wide association study (GWAS) data (2953 whites) were also used for in silico replication. The GWAS detected two BMD candidate genes, ADAMTS18 (ADAM metallopeptidase with thrombospondin type 1 motif, 18) and TGFBR3 (transforming growth factor, beta receptor III). Replication studies verified the significant findings by GWAS. We also detected significant associations with hip fracture for ADAMTS18 SNPs in the Chinese HF sample. Meta-analyses supported the significant associations of ADAMTS18 and TGFBR3 with BMD (p values: 2.56 × 10−5 to 2.13 × 10−8; total sample size: n = 5925 to 9828). Electrophoretic mobility shift assay suggested that the minor allele of one significant ADAMTS18 SNP might promote binding of the TEL2 factor, which may repress ADAMTS18 expression. The data from NCBI GEO expression profiles also showed that ADAMTS18 and TGFBR3 genes were differentially expressed in subjects with normal skeletal fracture versus subjects with nonunion skeletal fracture. Overall, the evidence supports that ADAMTS18 and TGFBR3 might underlie BMD determination in the major human ethnic groups. To identify and validate genes associated with bone mineral density (BMD), which is a prominent osteoporosis risk factor, we tested 379,319 SNPs in 1000 unrelated white U.S. subjects for associations with BMD. For replication, we genotyped the most significant SNPs in 593 white U.S. families (1972 subjects), a Chinese hip fracture (HF) sample (350 cases, 350 controls), a Chinese BMD sample (2955 subjects), and a Tobago cohort of African ancestry (908 males). Publicly available Framingham genome-wide association study (GWAS) data (2953 whites) were also used for in silico replication. The GWAS detected two BMD candidate genes, ADAMTS18 (ADAM metallopeptidase with thrombospondin type 1 motif, 18) and TGFBR3 (transforming growth factor, beta receptor III). Replication studies verified the significant findings by GWAS. We also detected significant associations with hip fracture for ADAMTS18 SNPs in the Chinese HF sample. Meta-analyses supported the significant associations of ADAMTS18 and TGFBR3 with BMD (p values: 2.56 × 10−5 to 2.13 × 10−8; total sample size: n = 5925 to 9828). Electrophoretic mobility shift assay suggested that the minor allele of one significant ADAMTS18 SNP might promote binding of the TEL2 factor, which may repress ADAMTS18 expression. The data from NCBI GEO expression profiles also showed that ADAMTS18 and TGFBR3 genes were differentially expressed in subjects with normal skeletal fracture versus subjects with nonunion skeletal fracture. Overall, the evidence supports that ADAMTS18 and TGFBR3 might underlie BMD determination in the major human ethnic groups. Osteoporosis (MIM 166710) is the most common metabolic skeletal disease; it is estimated that over 200 million people worldwide have osteoporosis.1Reginster J.Y. Burlet N. Osteoporosis: a still increasing prevalence.Bone. 2006; 38: S4-S9Abstract Full Text Full Text PDF PubMed Scopus (601) Google Scholar It is mainly characterized by low bone mass and microarchitectural deterioration of bone tissue, with the consequent increase in fragility and susceptibility to fractures.2Ray N.F. Chan J.K. Thamer M. Melton III, L.J. Medical expenditures for the treatment of osteoporotic fractures in the United States in 1995: report from the National Osteoporosis Foundation.J. Bone Miner. Res. 1997; 12: 24-35Crossref PubMed Scopus (1115) Google Scholar Bone mineral density (BMD) has a high heritability, ∼70%, and it is an important measurable risk factor for osteoporotic fractures, because these fractures can develop with even mild stress and trauma when BMD has decreased to the threshold point.3Cummings S.R. Black D. Bone mass measurements and risk of fracture in Caucasian women: a review of findings from prospective studies.Am. J. Med. 1995; 98: 24S-28SAbstract Full Text PDF PubMed Scopus (150) Google Scholar Consequently, BMD is the predominant surrogate phenotype used in studying osteoporosis. So far, several genes for osteoporosis have been established, mostly through the large-scale meta-analyses launched by the GENOMOS consortium. The examples include the associations of Estrogen Receptor-α (ESR1 [MIM 133430]) PvuII and XbaI SNPs with fracture risk, the association between the Cdx2 polymorphism of Vitamin D Receptor (VDR [MIM 601769]) and vertebral fracture risk, the association between the Sp1 polymorphism of Collagen Type I α-1 (COL1A1 [MIM 120150]) and BMD, and the associations between Low Density Lipoprotein Receptor-Related Protein 5 (LRP5 [MIM 603506]) SNPs and BMD.4Macdonald H.M. McGuigan F.E. Stewart A. Black A.J. Fraser W.D. Ralston S. Reid D.M. Large-scale population-based study shows no evidence of association between common polymorphism of the VDR gene and BMD in British women.J. Bone Miner. Res. 2006; 21: 151-162Crossref PubMed Scopus (77) Google Scholar, 5Ralston S.H. Uitterlinden A.G. Brandi M.L. Balcells S. Langdahl B.L. Lips P. Lorenc R. Obermayer-Pietsch B. Scollen S. Bustamante M. et al.Large-scale evidence for the effect of the COLIA1 Sp1 polymorphism on osteoporosis outcomes: the GENOMOS study.PLoS Med. 2006; 3: e90Crossref PubMed Scopus (155) Google Scholar, 6Ioannidis J.P. Ralston S.H. Bennett S.T. Brandi M.L. Grinberg D. Karassa F.B. Langdahl B. van Meurs J.B. Mosekilde L. Scollen S. et al.Differential genetic effects of ESR1 gene polymorphisms on osteoporosis outcomes.JAMA. 2004; 292: 2105-2114Crossref PubMed Scopus (261) Google Scholar, 7van Meurs J.B. Trikalinos T.A. Ralston S.H. Balcells S. Brandi M.L. Brixen K. Kiel D.P. Langdahl B.L. Lips P. Ljunggren O. et al.Large-scale analysis of association between LRP5 and LRP6 variants and osteoporosis.JAMA. 2008; 299: 1277-1290Crossref PubMed Scopus (199) Google Scholar, 8Uitterlinden A.G. Ralston S.H. Brandi M.L. Carey A.H. Grinberg D. Langdahl B.L. Lips P. Lorenc R. Obermayer-Pietsch B. Reeve J. et al.The association between common vitamin D receptor gene variations and osteoporosis: a participant-level meta-analysis.Ann. Intern. Med. 2006; 145: 255-264Crossref PubMed Scopus (214) Google Scholar However, the majority of the genetic factors that influence BMD variation remain unknown.9Liu Y.J. Shen H. Xiao P. Xiong D.H. Li L.H. Recker R.R. Deng H.W. Molecular genetic studies of gene identification for osteoporosis: a 2004 update.J. Bone Miner. Res. 2006; 21: 1511-1535Crossref PubMed Scopus (102) Google Scholar, 10Liu Y.Z. Liu Y.J. Recker R.R. Deng H.W. Molecular studies of identification of genes for osteoporosis: the 2002 update.J. Endocrinol. 2003; 177: 147-196Crossref PubMed Scopus (204) Google Scholar The goal of this study was to identify, by use of a genome-wide association study (GWAS) and replication approaches, genes influencing human BMD variation at the hip and spine, the clinically most important skeletal sites. The clinical characteristics of participants in five independent cohorts—the white U.S. GWAS sample (n = 1000), the white U.S. family sample (n = 1972), the Chinese hip fracture (HF) sample (n = 700), the Chinese BMD sample (n = 2995), and the Tobago cohort of African origin (n = 908 men)—are described in Table 1, Table 2, Table 3, Table 4, Table 5. Except for the white U.S. family sample, all samples were population-based. The publicly shared Framingham 550K GWAS data from the family-based Framingham Osteoporosis Study (n = 2953 white subjects) were also analyzed for the replication SNPs.Table 1Characteristics of White U.S. GWAS SampleTraitMaleFemale≤50 years (n = 250)>50 years (n = 251)Premenopause (n = 249)Postmenopause (n = 250)Age (years)33.44 (9.66)67.33 (6.74)33.97 (8.45)66.36 (5.67)Height (cm)180.00 (6.78)175.67 (6.63)165.38 (6.13)162.22 (6.43)Weight (kg)88.03 (15.35)90.04 (14.47)70.74 (16.51)71.71 (15.10)Spine BMD (g/cm2)1.054 (0.123)1.085 (0.203)1.045 (0.118)0.944 (0.102)Hip BMD (g/cm2)1.066 (0.146)1.010 (0.141)0.953 (0.123)0.861 (0.135)n = 1000, data are shown as mean (SD). Open table in a new tab Table 2Characteristics of White U.S. Family SampleTraitSons (n = 246)Daughters (n = 895)Fathers (n = 318)Mothers (n = 513)Age (years)38.7 (11.0)39.1 (10.3)63.6 (9.9)62.3 (10.6)Height (cm)179.1 (7.5)164.8 (6.1)176.3 (7.1)162.5 (6.3)Weight (kg)90.1 (17.3)71.7 (16.0)90.7 (16.1)73.14 (14.9)Spine BMD (g/cm2)1.06 (0.14)1.05 (0.13)1.06 (0.14)0.97 (0.16)Hip BMD (g/cm2)1.06 (0.13)0.97 (0.13)1.01 (0.17)0.88 (0.14)n = 1972, data are shown as mean (SD). Open table in a new tab Table 3Characteristics of Chinese HF SampleCaseControlNumber350350Sex ratio (M/F)124/226173/177Age (years)69.35 (7.41)69.54 (6.09)Weight (kg)59.15 (12.05)59.61 (10.84)Height (cm)162.84 (8.31)159.41 (9.20)n = 700, data are shown as mean (SD). Open table in a new tab Table 4Characteristics of Chinese BMD SampleTraitMaleFemale≤50 years (n = 1298)>50 years (n = 139)Premenopause (n = 1149)Postmenopause (n = 369)Age (years)26.78 (4.53)65.59 (8.59)27.38 (6.30)60.50 (8.02)Height (cm)169.92 (5.57)166.95 (5.61)158.71 (5.11)156.26 (5.48)Weight (kg)63.37 (9.00)70.22 (9.61)51.40 (6.71)59.70 (8.94)Spine BMD (g/cm2)0.98 (0.11)0.94 (0.15)0.94 (0.10)0.82 (0.14)Hip BMD (g/cm2)0.98 (0.13)0.91 (0.13)0.88 (0.10)0.81 (0.13)n = 2995, data are shown as mean (SD). Open table in a new tab Table 5Characteristics of Tobago Cohort of African OriginAge (yr)56.2 (9.6)Height (cm)175.5 (6.9)Weight (kg)84.47 (14.79)Total body BMD (g/cm2)1.27 (0.11)Spine BMD (g/cm2)1.12 (0.16)Hip BMD (g/cm2)1.15 (0.14)Femoral neck BMD (g/cm2)1.01 (0.15)Trochanter BMD (g/cm2)0.89 (0.13)Intertrochanteric BMD (g/cm2)1.34 (0.16)Ward's Triangle BMD (g/cm2)0.85 (0.19)n = 908, all of which are men. Data are shown as mean (SD). Open table in a new tab n = 1000, data are shown as mean (SD). n = 1972, data are shown as mean (SD). n = 700, data are shown as mean (SD). n = 2995, data are shown as mean (SD). n = 908, all of which are men. Data are shown as mean (SD). During the discovery phase, we carried out a GWAS using the Affymetrix Gene Chip Human Mapping 500K Array Set. We successfully genotyped a total of 379,319 single-nucleotide polymorphisms (SNPs) in the white GWAS sample (1000 subjects), recruited from Midwestern U.S. for BMD analyses. The subject-recruitment procedures, standard examinations of BMD and related phenotypes, genotyping with Affymetrix 500K Array, genotyping quality control, and SNP-exclusion procedures have been detailed elsewhere.11Liu Y.J. Liu X.G. Wang L. Dina C. Yan H. Liu J.F. Levy S. Papasian C.J. Drees B.M. Hamilton J.J. et al.Genome-wide association scans identified CTNNBL1 as a novel gene for obesity.Hum. Mol. Genet. 2008; 17: 1803-1813Crossref PubMed Scopus (137) Google Scholar, 12Liu Y.Z. Wilson S.G. Wang L. Liu X.G. Guo Y.F. Li J. Yan H. Deloukas P. Soranzo N. Chinnapen-Horsley U. et al.Identification of PLCL1 gene for hip bone size variation in females in a genome-wide association study.PLoS. ONE. 2008; 3: e3160Crossref PubMed Scopus (50) Google Scholar, 13Yang T.L. Chen X.D. Guo Y. Lei S.F. Wang J.T. Zhou Q. Pan F. Chen Y. Zhang Z.X. Dong S.S. et al.Genome-wide copy-number-variation study identified a susceptibility gene, UGT2B17, for osteoporosis.Am. J. Hum. Genet. 2008; 83: 663-674Abstract Full Text Full Text PDF PubMed Scopus (159) Google Scholar In the GWAS sample, the hip and spine BMD data were adjusted by significant covariates, including age, sex, height, and weight, and analyzed with allelic and haplotypic association tests (haplotype trend regression [HTR]14Zaykin D.V. Westfall P.H. Young S.S. Karnoub M.A. Wagner M.J. Ehm M.G. Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals.Hum. Hered. 2002; 53: 79-91Crossref PubMed Scopus (580) Google Scholar) implemented in HelixTree 5.3.1. The association analyses were conducted in (1) the total sample, (2) the male and female subgroups, (3) the premenopausal white females, and (4) the postmenopausal white females, each group analyzed separately. Given the LD among SNPs across the whole genome, the Bonferroni correction could be considered overly conservative; therefore, we adopted the pointwise GWAS significance threshold proposed elsewhere,15Lencz T. Morgan T.V. Athanasiou M. Dain B. Reed C.R. Kane J.M. Kucherlapati R. Malhotra A.K. Converging evidence for a pseudoautosomal cytokine receptor gene locus in schizophrenia.Mol. Psychiatry. 2007; 12: 572-580Crossref PubMed Scopus (226) Google Scholar ∼4.2 × 10−7. The genewise approach used in calculating this threshold took into account recent estimates of the total number of genes in the human genome. Because 20 GWA tests (men/women/total samples; hip/spine BMDs; premenopausal/postmenopausal female samples; single-SNP testing/sliding-window testing) were conducted, the pointwise GWAS significance threshold that we used here was 2.1 × 10−8 (Bonferroni adjustment of 4.2 × 10−7). EIGENSTRAT16Price A.L. Patterson N.J. Plenge R.M. Weinblatt M.E. Shadick N.A. Reich D. Principal components analysis corrects for stratification in genome-wide association studies.Nat. Genet. 2006; 38: 904-909Crossref PubMed Scopus (6180) Google Scholar software was used for guarding against spurious associations due to potential population stratification. The LD patterns of the implicated genes were analyzed and plotted with the use of the Haploview program17Barrett J.C. Fry B. Maller J. Daly M.J. Haploview: analysis and visualization of LD and haplotype maps.Bioinformatics. 2005; 21: 263-265Crossref PubMed Scopus (11431) Google Scholar with the HapMap data from the International HapMap project. The FASTSNP program was used for predicting the function of the SNPs of interest.18Yuan H.Y. Chiou J.J. Tseng W.H. Liu C.H. Liu C.K. Lin Y.J. Wang H.H. Yao A. Chen Y.T. Hsu C.N. FASTSNP: an always up-to-date and extendable service for SNP function analysis and prioritization.Nucleic Acids Res. 2006; 34: W635-W641Crossref PubMed Scopus (437) Google Scholar We used five independent samples for replication. The first was a white U.S. family sample comprising 1972 white individuals, from 593 nuclear families, who were recruited and phenotyped in the same way as were those in the white U.S. GWAS sample.11Liu Y.J. Liu X.G. Wang L. Dina C. Yan H. Liu J.F. Levy S. Papasian C.J. Drees B.M. Hamilton J.J. et al.Genome-wide association scans identified CTNNBL1 as a novel gene for obesity.Hum. Mol. Genet. 2008; 17: 1803-1813Crossref PubMed Scopus (137) Google Scholar, 12Liu Y.Z. Wilson S.G. Wang L. Liu X.G. Guo Y.F. Li J. Yan H. Deloukas P. Soranzo N. Chinnapen-Horsley U. et al.Identification of PLCL1 gene for hip bone size variation in females in a genome-wide association study.PLoS. ONE. 2008; 3: e3160Crossref PubMed Scopus (50) Google Scholar Genotyping was performed by KBioscience (Herts, UK) via the technology of competitive allele-specific PCR (KASPar), which is detailed at the company's website. Five SNPs of interest (Table 6) were successfully genotyped. The replication rate (duplicate concordance rate) was 99.7% for the genotyping in the white family sample, and the average call rate was 97.8%.Table 6Summary of Association Results in GWAS and Replication StudiesSNPUS White GWAS Sample p ValueUS White Family Sample p ValueFramingham Sample (White) p ValueChinese HF Sample p ValueChinese BMD Sample p ValueTobago BMD Sample (African) p ValueADAMTS18rs16945612Hip BMD/female sample:5.75 × 10−7 (allele)4.61 × 10−4 (haplotype)Hip BMD:1.6 × 10−2Spine BMD:3.5 × 10−3Hip BMD: 6 × 10−3Hip fracture: 1.9 × 10−2Hip BMD:9 × 10−3 Spine BMD: 1 × 10−2Hip BMD: 1.7 × 10−1 Trochanter BMD: 3.2 × 10−2ADAMTS18rs11859065Hip BMD/female sample:1.28 × 10−6 (allele)4.91 × 10−4 (haplotype)Hip BMD:1.65 × 10−2 Spine BMD: 3.5 × 10−3Hip BMD: 5.5 × 10−3Hip fracture: 1.9 × 10−2Hip BMD:9 × 10−3 Spine BMD: 1 × 10−2NAars11859065, rs11864477 and rs11860781 was not genotyped in Tobago sample considering the redundancy in genotyping since they are all in strong LD with rs16945612 in the HapMap African sample.ADAMTS18rs11864477Hip BMD/female sample:4.17 × 10−7 (allele)2.90 × 10−5 (haplotype)Hip BMD:1.65 × 10−2 Spine BMD: 3.5 × 10−3Hip BMD: 6.5 × 10−3Hip fracture: 1.9 × 10−2Hip BMD:9 × 10−3 Spine BMD: 1 × 10−2NAars11859065, rs11864477 and rs11860781 was not genotyped in Tobago sample considering the redundancy in genotyping since they are all in strong LD with rs16945612 in the HapMap African sample.ADAMTS18rs11860781Hip BMD/female sample:2.03 × 10−6 (allele)5.78 × 10−4 (haplotype)Hip BMD: 1 × 10−2Hip BMD: 1.0 × 10−2Hip fracture: 1.7 × 10−1Hip BMD: 1 × 10−1NAars11859065, rs11864477 and rs11860781 was not genotyped in Tobago sample considering the redundancy in genotyping since they are all in strong LD with rs16945612 in the HapMap African sample.TGFBR3rs17131547Spine BMD/total sample:3.91 × 10−4 (allele)3.47 × 10−8 (haplotype)Spine BMD: 1 × 10−2Spine BMD: 3 × 10−2NAbrs17131547 was monomorphic in Chinese.NAbrs17131547 was monomorphic in Chinese.Spine BMD: 6.7 × 10−3 Total body BMD: 3.1 × 10−2Hip BMD: 1.1 × 10−3Femoral Neck BMD: 5.4 × 10−3Intertrochanter BMD: 4.93 × 10−4Trochanter BMD: 1.3 × 10−2Ward's triangle BMD: 2.82 × 10−4a rs11859065, rs11864477 and rs11860781 was not genotyped in Tobago sample considering the redundancy in genotyping since they are all in strong LD with rs16945612 in the HapMap African sample.b rs17131547 was monomorphic in Chinese. Open table in a new tab The second replication cohort was the Framingham sample from the Framingham Osteoporosis Study,19Cupples L.A. Arruda H.T. Benjamin E.J. D'Agostino Sr., R.B. Demissie S. DeStefano A.L. Dupuis J. Falls K.M. Fox C.S. Gottlieb D.J. et al.The Framingham Heart Study 100K SNP genome-wide association study resource: overview of 17 phenotype working group reports.BMC Med. Genet. 2007; 8: S1Crossref PubMed Scopus (147) Google Scholar which has been detailed before.20Hannan M.T. Felson D.T. Anderson J.J. Bone mineral density in elderly men and women: results from the Framingham osteoporosis study.J. Bone Miner. Res. 1992; 7: 547-553Crossref PubMed Scopus (224) Google Scholar, 21Hannan M.T. Felson D.T. Dawson-Hughes B. Tucker K.L. Cupples L.A. Wilson P.W. Kiel D.P. Risk factors for longitudinal bone loss in elderly men and women: the Framingham Osteoporosis Study.J. Bone Miner. Res. 2000; 15: 710-720Crossref PubMed Scopus (564) Google Scholar Genotype and phenotype data were downloaded from the dbGaP database. Data download and usage was authorized by the SHARe data-access committee. We have the data on 2953 phenotyped white subjects, 448 from the original cohort (160 men and 288 women) and 2505 from the offspring cohort (1114 men and 1391 women). The original-cohort participants had BMD measurements calculated via a dual X-ray absorptiometry machine (Lunar DPX-L), performed at the hip and spine during exam 24. The offspring-cohort participants were scanned with the same machine at exam 6 or 7. The Framingham sample was genotyped with the use of approximately 550,000 SNPs (Affymetrix 500K mapping array plus Affymetrix 50K supplemental array). The genotype data for the five SNPs of interest (Table 6) were analyzed for BMD associations. The third replication cohort was a Chinese HF sample, recruited from Xi'an City and neighboring areas in China. The sample consisted of 350 unrelated patients with osteoporotic HF and 350 unrelated controls without HF. The subject recruitment and experimentation procedures (including genotyping) have been described by Yang et al.,13Yang T.L. Chen X.D. Guo Y. Lei S.F. Wang J.T. Zhou Q. Pan F. Chen Y. Zhang Z.X. Dong S.S. et al.Genome-wide copy-number-variation study identified a susceptibility gene, UGT2B17, for osteoporosis.Am. J. Hum. Genet. 2008; 83: 663-674Abstract Full Text Full Text PDF PubMed Scopus (159) Google Scholar who called the same cohort a “Chinese GWA sample.” The genotype data for the four SNPs of interest (Table 6) were analyzed for HF associations. The fourth replication sample, the Chinese BMD sample, comprised 2955 Chinese adults living in Changsha City of China. The subject-recruitment criteria were the same as those adopted for the white U.S. samples. BMD was measured with the same model Hologic 4500W machines (Hologic, Bedford, MA, USA) under the same strict protocols applied for the white U.S. samples. The coefficient of variation (CV) values of the dual-energy X-ray absorptiometry (DXA) measurements for hip and spine BMDs were approximately 1.01% and 1.33%, respectively. Genotyping was performed with the use of a primer-extension method, with MALDI-TOF mass spectrometry for multiplexed genotyping of SNPs on a MassARRAY system, performed as suggested by the manufacturer (Sequenom, San Diego, CA) and well described by Braun et al.22Braun A. Roth R. McGinniss M.J. Technology challenges in screening single gene disorders.Eur. J. Pediatr. 2003; 162: S13-S16Crossref PubMed Scopus (12) Google Scholar Four SNPs of interest (Table 6) were successfully genotyped. The replication rate is 99.2%, and the average call rate is 97.2%. The fifth replication sample was the Tobago BMD sample, comprising 908 men of West African ancestry who were randomly selected from a large population-based study of BMD among 2501 men aged 40 and older on the Caribbean island of Tobago.23Hill D.D. Cauley J.A. Sheu Y. Bunker C.H. Patrick A.L. Baker C.E. Beckles G.L. Wheeler V.W. Zmuda J.M. Correlates of bone mineral density in men of African ancestry: the Tobago bone health study.Osteoporos. Int. 2008; 19: 227-234Crossref PubMed Scopus (47) Google Scholar This sample was of West African ancestry with low non-African admixture (6% non-African).24Miljkovic-Gacic I. Ferrell R.E. Patrick A.L. Kammerer C.M. Bunker C.H. Estimates of African, European and Native American ancestry in Afro-Caribbean men on the island of Tobago.Hum. Hered. 2005; 60: 129-133Crossref PubMed Scopus (65) Google Scholar The detailed recruitment scheme and phenotyping procedures have been described elsewhere.23Hill D.D. Cauley J.A. Sheu Y. Bunker C.H. Patrick A.L. Baker C.E. Beckles G.L. Wheeler V.W. Zmuda J.M. Correlates of bone mineral density in men of African ancestry: the Tobago bone health study.Osteoporos. Int. 2008; 19: 227-234Crossref PubMed Scopus (47) Google Scholar The two SNPs of interest (Table 6) were successfully genotyped with the fluorogenic 5′-nuclease TaqMan allelic-discrimination assay system (Applied Biosystems, Foster City, CA). The assays were performed under standard conditions on a 7900HT real-time PCR instrument. All genotype calls were determined by two independent investigators, and only concordant calls were used. The genotyping consensus rate, based on approximately 8% blind replicate genotypes, was 99.7%. The average completeness of genotyping for the two markers was 98.3%. In all studies, informed consent was obtained from participants and studies were approved by the local institutional review boards or ethical committees. Statistical analyses for replication samples involved the following: (1) In the white U.S. family sample and the Framingham Osteoporosis Study sample, we conducted the family-based association test (FBAT)25Lange C. DeMeo D.L. Laird N.M. Power and design considerations for a general class of family-based association tests: quantitative traits.Am. J. Hum. Genet. 2002; 71: 1330-1341Abstract Full Text Full Text PDF PubMed Scopus (109) Google Scholar for the SNPs of interest for their association with the BMD residuals adjusted by significant covariates, including age, sex, height, and weight. (2) In the Chinese HF sample, the genotype distributions of ADAMTS18 SNPs between fracture and nonfracture groups were analyzed with logistic regression models controlling for age, sex, height, and weight as covariates. (3) In the Chinese BMD sample, the statistical procedures were the same as those used for the white U.S. GWAS sample. (4) In the Tobago cohort comprising only men, SNPs were tested for association with BMD via linear regression as a test for an additive association between the number of copies of the minor allele and BMD. The models were adjusted for age, weight, and height. Analyses were performed with SAS version 9.1 (SAS Institute, Cary, NC, USA). The magnitude and direction of SNP effects were estimated by a linear-regression model for random samples and by a quantitative transmission-disequilibrium test (QTDT) for family samples. Finally, the meta-analyses for the significant SNPs from (1) all of the three white BMD samples (white U.S. GWAS, white U.S. family, and Framingham samples) and (2) all of the five BMD samples from different ethnic origins (GWAS, white U.S. family, Framingham, Chinese BMD, and Tobago samples) were conducted, respectively, with the weighted z score-based meta-analysis approach26Whitlock M.C. Combining probability from independent tests: the weighted Z-method is superior to Fisher's approach.J. Evol. Biol. 2005; 18: 1368-1373Crossref PubMed Scopus (500) Google Scholar, 27Zeggini E. Scott L.J. Saxena R. Voight B.F. Marchini J.L. Hu T. de Bakker P.I. Abecasis G.R. Almgren P. Andersen G. et al.Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes.Nat. Genet. 2008; 40: 638-645Crossref PubMed Scopus (1442) Google Scholar (weighted by the square root of the sample size of each combining sample) used for quantification of the overall evidence for association with BMD variation. The initial GWAS results were as follows: For the single-SNP allelic analyses, we did not find any significant associations with hip/spine BMD in either the total GWAS sample or the male subsample at the genome-wide threshold of 2.1 × 10−8. In females, although no GWAS-level significant association with BMD was found, the SNP rs11864477 in the ADAMTS18 gene (ADAM metallopeptidase with thrombospondin type 1 motif, 18 [MIM 607512]) associated with hip BMD (p = 4.17 × 10−7, Figure 1A, Table 6) at the closest level to the genome-wide significance threshold. In the sliding-window haplotype analyses, the most significant haplotype for spine BMD almost hit the GWAS-significance cutoff. This haplotype was located in the TGFBR3 gene (transforming growth factor, beta receptor III [MIM 600742]) (p = 3.47 × 10−8; Figure 1B, Table 6). We then analyzed the above two implicated genes in more detail. In the female sample, as shown in Figure 2 and Table 6, three other ADAMTS18 gene SNPs, which are near and in significantly strong LD with rs11864477 (pairwise r2 > 0.90), were associated with hip BMD (p values = 2.03 × 10−6, 5.75 × 10−7, and 1.28 × 10−6 for rs11860781, rs16945612, and rs11859065, respectively). These four SNPs were suggestive for hip BMD in the total sample (p values = 8.31 × 10−4, 3.84 × 10−3, 1.98 × 10−3, and 1.66 × 10−3 for rs11864477, rs11860781, rs16945612, and rs11859065, respectively). Haplotype block 12, containing rs16945612, rs11864477, and rs11859065, was suggestively significant for hip BMD in the female subgroup (p = 9.95 × 10−6) and the total sample (p = 1.9 × 10−2) (Figure 2). In the male sample, we detected a significant haplotype window that contained rs11860781 (highly correlated with rs16945612, rs11864477, and rs11859065 [r2 > 0.8]) and was suggestively associated with hip BMD (p = 6 × 10−3). Analyses stratified by menopausal status showed consistent results. All of these four highly correlated SNPs were suggestively associated with hip BMD in the postmenopausal white women (p values = 2 × 10−3 for all four SNPs) and in the premenopausal white women (p = 4 × 10−3 for rs11864477; p = 6 × 10−3 for rs16945612; p = 1 × 10−2 for rs11860781 and rs11859065). These data support the proposal that the ADAMTS18 gene contributes to the variation of hip BMD. For the TGFBR3 gene, we found that rs17131547 was the key SNP for the most significant haplotype window (p = 3.47 × 10−8 for spine BMD association), composed of TGFBR3 SNPs—rs17131547, rs12403389, rs4658112, rs17131544, and rs2087299. Several other haplotype windows harboring rs17131547 were also suggestively significant for spine BMD (p values lie in [0.005, 0.05]). Single-SNP analyses showed that rs17131547 was suggestive for spine BMD in the total sample (p = 3.91 × 10−4; Figure 3 and Table 6), the male sample (p = 4.27 × 10−3), and the female sample (p = 3.8 × 10−2). Interestingly, no adjacent SNPs near rs17131547 were significant for spine BMD (Figure 3 and Table S2, available online). LD analyses showed that rs17131547 was an independent SNP with almost no LD with any of the other typed SNPs in the TGFBR3 gene (pairwise r2 < 0.04), suggesting the independent association of this SNP or a nearby untyped SNP with spine BMD. The detailed information and association results for both ADAMTS18 and TGFBR3 are summarized in Tables S1 and S2. In the white U.S. GWAS sample, we compared raw BMD values between the groups carrying different alleles of the two most significant BMD-associated SNPs. As shown in Figure 4, subjects carrying the C allele of rs11864477 in ADAMTS18 had a significantly lower mean hip BMD value than those carrying the alternative T allele (3% lower; raw hip BMD values were 0.

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