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Parathyroid hormone gene with bone phenotypes in Chinese
BBRC Biochemical and Biophysical Research Communications 307 (2003) 666–671 www.elsevier.com/locate/ybbrc
Parathyroid hormone gene with bone phenotypes in Chinese Xiao-Gang Zhou,a Yao-Zhong Liu,b Miao-Xin Li,a Wei-Xia Jian,a Shu-Feng Lei,a Yue-Juan Qin,c Qi Zhou,c and Hong-Wen Denga,b,* a
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, PR China b Osteoporosis Research Center and Department of Biomedical Sciences, Creighton University Medical Center, 601 N. 30th St., Suite 6787, Omaha, NE 68131, USA c The 6th People’s Hospital of Shanghai, Shanghai 200233, PR China Received 12 June 2003
Abstract Osteoporosis is a common disorder afflicting old people. The parathyroid hormone (PTH) gene is involved in bone remodeling and calcium homeostasis, and has been considered as an important candidate gene for osteoporosis. In this study, we simultaneously tested linkage and/or association of PTH gene with bone mineral density (BMD) and bone mineral content (BMC), two important risk factors for osteoporosis. A sample of 1263 subjects from 402 Chinese nuclear families was used. The families are composed of both parents and at least one healthy daughter aged from 20 to 45 years. All the subjects were genotyped at the polymorphic BstBI site inside the intron 2 of the PTH gene (a nucleotide substitution of G to A at the position +3244). BMD and BMC were measured at the lumbar spine and the hip region via dual-energy X-ray absorptiometry (DXA). Using QTDT (quantitative trait transmission disequilibrium test), we did not find significant results for association or linkage between the PTH gene and BMD or BMC variation at the spine or hip. Our data do not support the PTH gene as a quantitative trait locus (QTL) underlying the bone phenotypic variation in the Chinese population. Ó 2003 Elsevier Inc. All rights reserved. Keywords: Analysis of covariance; Association; Bone mineral content; Bone mineral density; Linkage; The parathyroid hormone gene; Transmission disequilibrium test
Osteoporosis is a common disorder afflicting old people [1,2]. It was estimated that for 60-year-old Caucasian women and men, the risk for an osteoporotic fracture (OF) was 60% and 30%, respectively, for their remaining lifetime [3]. Bone mineral density (BMD) and bone mineral content (BMC) are important risk factors for OFs [4–7]. Extensive studies have been performed in Caucasians to test candidate genes against BMD or BMC variation through traditional association or linkage approaches. Few studies have been done through the contemporary transmission disequilibrium test (TDT), which is robust to population stratification [8]. Parathyroid hormone (PTH) is an 84-amino-acid polypeptide hormone. It has significant effects on bone * Corresponding author. Fax: 1-402-280-5034. E-mail address: [email protected] (H.-W. Deng).
0006-291X/03/$ - see front matter Ó 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0006-291X(03)01261-0
metabolism [9]. Upon PTH binding to its receptor and activation of G proteins, a signal transduction cascade through the cAMP/protein kinase A (PKA) pathway [10], the protein kinase C (PKC) pathway [11], or calcium pathway is initiated that ultimately leads to changes in osteoblastic function [12]. Activation of osteoblasts by PTH results in expression of genes important for the degradation of the extracellular matrix, production of growth factors, and stimulation and recruitment of osteoclasts. The overall effect of PTH is to raise plasma levels of calcium, partly through bone resorption [13]. Studies on mice also showed that PTH plays an important role to stimulate osteoclast formation and bone resorption [14]. The human PTH gene is localized in 11p15.3-p15.1 [15]. The nucleotide substitutions of G to A at the position +3244 is defined by the BstBI restriction fragment length polymorphism (RFLP) inside the PTH gene [16].
X.-G. Zhou et al. / Biochemical and Biophysical Research Communications 307 (2003) 666–671
The PTH gene has been considered as an important candidate gene for osteoporosis. Yet only a few studies have been performed on the relationship of the PTH gene polymorphism and bone mass variation [17–20]. In Chinese, there has been no such study reported on the relationship of PTH gene and bone mass variation. Three approaches have been employed to identify genes underlying complex trait variation: association, linkage, and TDT analysis. The finding of an association only represents a tentative evidence that a marker is linked to a disease gene, since population stratification may give rise to spurious association [21]. The linkage study has limited statistical power when employed to a complex trait [22,23]. As a result, linkage findings are difficult to replicate across studies [24]. The TDT is a family-based test of association and widely used to search for the genetic factors in diseases. It compares alleles transmitted vs. those non-transmitted from parents to affected offspring. It is robust to population stratification that can easily lead to spurious association [25]. Provided that an association is present, the TDT often has more power than conventional linkage tests [22,23,25,26]. Given the potential importance of PTH in bone remodeling and calcium homeostasis, we use the conventional linkage and association (total-family association and analysis of covariance) approaches as well as the more contemporary TDT (within-family association) approach [8] to test the PTH gene as a quantitative trait locus (QTL) underlying the bone phenotypic variation (BMD and BMC) in the Chinese population.
Materials and methods Subjects. The study was approved by the Research Administration Departments of Hunan Normal University and the 6th People’s Hospital of Shanghai, PR China. We have recruited 1263 subjects from 402 nuclear families with both parents and at least one healthy daughter (whose ages range from 20 to 45). All the study subjects belong to the Chinese Han ethnic group. The nuclear families vary in size from 3 to 6 individuals, with a mean of 3.14 individuals. The numbers of families with one daughter, two daughters, three daughters, and four daughters are 350, 48, 3, and 1, respectively. All the subjects were recruited by the 6th People’s Hospital of Shanghai from a local population of the City of Shanghai located on the Mid-East Coast of PR China, and signed informed-consent documents before entering the project. We adopted the exclusion criteria defined in detail by Deng et al. [19] for daughters to minimize any known potential confounding effects on the bone phenotypes. PCR-RFLP. Genomic DNA was isolated according to the phenol–chloroform extraction protocols [27]. Genomic DNA (0.1–0.3 lg) was amplified in 25 ll of buffer solution (10 mM Tris–HCl [pH 9.0], 50 mM KCl, 0.1% Triton X-100, 0.9 mM MgCl2 , and 240 lM each of four deoxyribonucleotides). One unit of Taq polymerase (Sangon, Shanghai, PR China) and 0.52 lM each of oligonucleotide primer (the forward in intron 1: 50 -CAT TCT GTG TAC TAT AGT TTG30 , the reverse in the 30 flank region: 50 -GAG CTT TGA ATT AGC AGC ATG-30 ) were used in the reaction to generate a DNA fragment of 600 bp with BstBI RFLP inside the intron 2 of the PTH gene.
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Polymerase chain reaction (PCR) was performed in 38 cycles as follows: denaturation at 95 °C for 30 s, annealing at 50 °C for 30 s, and extension at 72 °C for 60 s on a PE9700 Thermal Cycler (Perkin Elmer Cetus, Norwalk, CT). After amplification, the PCR product was digested with restriction endonuclease BstBI (NEB Biotech., England) for 4 h at 65 °C and electrophoresed in a 2% agarose gel (Shanghai Yito Enterprise, Shanghai, PR China), stained by ethidium bromide, and then visualized under UV light. The RFLP polymorphisms of PTH BstBI were represented as B and b (B: 387 + 213 bp; b: 600 bp) [28]. Measurement. BMD (g/cm2 ) and BMC (g) of the spine (L1–L4), femoral neck, trochanter, intertrochanteric region, Ward’s triangle, and total hip (including femoral neck, trochanter, and intertrochanteric region) were measured by a Hologic QDR 2000+ dual-energy Xray absorptiometry (DXA) scanner (Hologic, Waltham MA). The scanner was calibrated daily, and the coefficient of variability (CV) values, which were obtained from seven individuals repeatedly measured for five times, of the DXA measurement at the spine (L1–L4), femoral neck, trochanter, intertrochanteric region, Ward’s triangle, and total hip, were 0.9%, 1.93%, 1.48%, 1.31%, 3.58%, and 0.8%, respectively, for BMD, and 1.32%, 2.59%, 4.74%, 2.45%, 4.51%, and 1.61%, respectively, for BMC. Weight and height were obtained at the same visit when the bone mass was measured. ANCOVA and other regular statistical analyses. Regular statistical analyses were conducted using the SAS program (SAS Institute, Cary, NC, USA). Association of the BstBI polymorphism with bone phenotypes in the mother group was tested with ANCOVA analysis (analysis of covariance). The Hardy–Weinberg distribution of the BstBI marker genotypes was tested with v2 test. Homogeneity of variance and fitted distribution of normal test of BMD and BMC within each of the three PTH BstBI genotypes among fathers, mothers, and daughters were performed with Bartlett’s test and Shapiro–Wilks W test, respectively. The phenotypic values of the trochanter BMD, Ward’s triangle BMD, spine BMC, and Ward’s triangle BMC were logarithm transformed because of the significant violation of normal distribution of these raw values. QTDT analyses. Tests of stratification, within-family association (TDT), total-family association, and linkage between BstBI RFLP and bone mass phenotypes (BMD and BMC) of the above-mentioned six skeletal sites were performed with the program QTDT (quantitative trait transmission disequilibrium test), which is available at the web site (http://www.well.ox.ac.uk/asthma/QTDT). According to Abecasis et al. [29], association can be partitioned into orthogonal between-family (b) and within-family (w) components. The former was sensitive to population structure and the latter was significant only in the presence of linkage disequilibrium and linkage. Since the test of total association evaluates association at population level on all the subjects by using all information including within- and between-family components, it may produce misleading results in the case of population stratification. Linkage analysis in the QTDT is based on the identity-by-descent (IBD) relationship of genotypes among sib pairs and the variance component framework using the likelihood ratio test. The QTDT provides the test of population stratification by evaluating whether the between-family (b) component is equal to within-family association (w) component [29]. Population stratification may only have impact on the between- but not within-family-component estimation [29]. Age, weight, and height are considered as covariates that may have significant effects on the bone phenotypic variation [30]. We used them to adjust for the raw bone phenotypic values before we performed the linkage and/or association tests in order to improve the statistical power by decreasing the effects of the random environmental factors on phenotypic variation and increasing the genetic signal to noise ratio (i.e., h2 estimate) [30]. Since all the offspring were females in the nuclear families, and the effects of parents’ phenotypes were excluded in the QTDT, the sex was not considered as covariates to adjust for the daughters’ bone phenotypes.
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Results The basic characteristics of the study subjects These data are shown in Table 1. There were 769 parents and 459 daughters included. Thirty-five parental bone phenotypic values were not obtained; therefore the number of parents with phenotypes (n ¼ 769) was less than that of parent with genotypes (n ¼ 804). The ages of parents and daughters are 60.8 6.8 years and 31.4 5.8 years (mean SD), respectively. The genotypes and allele frequencies Initially 804 parents and 459 daughters were used for genotyping. Three daughters’ genotypes failed to pass the Mendelian inheritance check within nuclear families. Four daughters’ samples were not amplified in PCR
after three repeated experiments due to the poor quality of DNA. Table 2 shows the data of 804 parents in our sample. The genotype frequencies within the parent group for the BB, Bb, and bb subjects are 73.5%, 24.8%, and 1.7%, respectively. The distribution of the genotypes (within parents) does not deviate from Hardy–Weinberg distribution (p ¼ 0:55). In Table 2, we also show the genotypes and the allele frequencies detected by two other studies. In Japanese postmenopausal women, the frequencies for BB, Bb, and bb are 82.5%, 16.7%, and 0.8%, respectively [17]. In the Caucasians of European origin, the corresponding data are 17%, 54%, and 29% [19], respectively. Our genotypes and allele frequencies in Chinese are a little different from those of Japanese and depart more drastically from that of Caucasians (v2 test, p < 0:001). It indicates that the genotype and allele frequency distribution for the PTH gene BstBI marker might be specific to different ethnic backgrounds. ANCOVA analyses
Table 1 Basic characteristics of parents and daughters Parents (n ¼ 769)
Daughters (n ¼ 459)
Age (year) Height (cm) Weight (kg)
60.8 6.8 160.4 8.2 63.9 10.4
31.4 5.8 159.9 5.2 55.1 8.0
BMD (g/cm2 ) Spine Femoral neck Trochanter Intertrochanter region Ward’s triangle Total hip
0.872 0.161 0.714 0.124 0.597 0.116 0.953 0.170 0.530 0.150 0.812 0.143
0.960 0.100 0.776 0.100 0.637 0.089 0.998 0.130 0.711 0.130 0.855 0.110
BMC (g) Spine Femoral neck Trochanter Intertrochanter region Ward’s triangle Total hip
52.258 14.381 3.663 0.772 6.651 1.945 20.029 5.908 0.612 0.194 30.343 8.218
55.451 8.770 3.695 0.530 6.101 1.170 17.460 3.280 0.867 0.180 27.256 4.440
Note. The BMD and BMC values (means SD) are raw values at the spine or hip.
The phenotype distribution (mean SD) among each genotype of the mother group is displayed in Table 3. As the number of bb subjects is too small (only 5) in our samples, we compared only BB and Bb subjects here. The BMD and BMC values are adjusted with age, weight, and height. Using the ANCOVA, marginal significant genotype–phenotype association (p ¼ 0:07) was detected in the mother group for the Ward’s triangle BMD. The association is not significant for other regions. However, there is a clear trend in these regions that the BB subjects tend to have higher BMD or BMC values than the Bb subjects. The observed mean BMD or BMC values in all the regions examined for the BB group are higher than those for the Bb group. QTDT analyses In QTDT analyses, three nuclear families were excluded in the final analyses because their daughters’ genotypes failed to pass the Mendelian inheritance
Table 2 Allele and genotype frequency distributions in Chinese, Japanese, and Caucasians Chinese (804)
Japanese (383)
Caucasians (620)
Allele frequencies
B ¼ 0:859 b ¼ 0:141
B ¼ 0:909 b ¼ 0:091
B ¼ 0:440 b ¼ 0:560
Genotype frequencies
BB ¼ 0:735 Bb ¼ 0:248 bb ¼ 0:017
BB ¼ 0:825 Bb ¼ 0:167 bb ¼ 0:008
BB ¼ 0:170 Bb ¼ 0:540 bb ¼ 0:290
p ¼ 0:55
p ¼ 0:92
p ¼ 0:03
p value of H.-W. test
2
p value
p < 0:001
Note. Hardy–Weinberg ratio is tested with v test. The data within the parentheses are the number of the study subjects. In the second column, all of the 804 parents in our samples are genotyped and corresponding data are shown here. In the fifth column, the p value shows significant difference (v2 test, p < 0:001) in genotype frequency distribution observed among the Chinese, Japanese, and the Caucasians. The data for the Japanese are cited from Hosoi et al. [17]. The data for the Caucasians are cited from Deng et al. [19].
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Table 3 ANCOVA test of bone phenotypes of the mother group p values
Genotype BB (n ¼ 293)
Bb (n ¼ 83)
2
BMD (g/cm ) Spine Femoral neck Trochanter Intertrochanter region Ward’s triangle Total hip
0.817 0.120 0.682 0.103 0.549 0.086 0.886 0.125 0.514 0.130 0.754 0.103
0.804 0.128 0.662 0.096 0.534 0.086 0.865 0.122 0.485 0.130 0.736 0.103
0.43 0.10 0.16 0.19 0.07 0.18
BMC (g) Spine Femoral neck Trochanter Intertrochanter region Ward’s triangle Total hip
44.514 9.159 3.248 0.454 5.378 0.993 15.986 2.763 0.599 0.171 24.612 3.722
43.449 9.171 3.177 0.455 5.248 0.994 15.914 2.768 0.567 0.172 24.339 3.728
0.35 0.21 0.30 0.84 0.13 0.56
Note. The BMD and BMC (means SD) values are adjusted by age, weight, and height. Mothers with bb genotypes are excluded here because the number of them is only five in our sample. Significance level is set at p < 0:05.
check. The genotypic values of the four daughters, whose samples were not amplified in PCR, were coded as zero (0). Thirty-five missing parental bone phenotypic values were coded as an unusual number (i.e., -x99.999). Because the effects of the parental phenotypes were excluded in the analyses, these missing values have no effect on our results. Therefore, 399 families with 1254 individuals are included here. The phenotypes used for linkage and TDT analyses are those of daughters. Using the QTDT program, we did not detect any significant population stratification in our samples, and found no significant association (including within-family association and total-family association) or linkage between the PTH BstBI marker polymorphism and the bone mass variation at the spine and the hip (Table 4).
Discussion BMD and BMC have been regarded as important determinants of OFs [6,7,31,32]. In recent years, extensive efforts have been made to find and confirm genes or genomic regions underlying BMD and BMC variation by applying linkage or association approaches in Caucasians [7,19,32]. However, few such studies have been conducted in Chinese population. In this study, using a more contemporary statistical method, TDT, we studied the PTH gene as a candidate gene underlying BMD and BMC variation at the spine and hip in 402 Chinese nuclear families. After adjusting for the covariates of age, height, and weight, we did not find significant association between the PTH BstBI polymorphisms and BMD/BMC variation at the spine or hip.
Table 4 Results of tests of population stratification, within-family association, total-family association, and linkage Test of population stratification
Test of within-family association
Test of total-family association
Test of linkage
BMD Spine emoral neck Trochanter Intertrochanter Ward’s triangle Total hip
0.05 0.69 0.81 0.58 0.81 0.68
1.00 0.20 0.57 0.51 0.16 0.41
1.00 1.00 1.00 1.00 1.00 1.00
0.73 1.00 1.00 1.00 0.78 1.00
BMC Spine Femoral neck Trochanter Intertrochanter Ward’s triangle Total hip
0.92 0.48 0.68 0.45 0.33 0.37
1.00 0.26 0.84 0.65 0.44 0.70
1.00 1.00 1.00 1.00 1.00 1.00
0.49 1.00 0.61 1.00 0.38 0.46
Note. All the tests are conducted by employing the program QTDT. The phenotypic values are adjusted for significant covariates of age, height, and weight. Values presented are the p values of given v2 tests.
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PTH plays an important role in bone remodeling and calcium homeostasis. Several polymorphisms (e.g., DraII, NlaIV, BstBI, and TaqI polymorphisms) have been identified inside the PTH gene [28]. A few studies have been performed on the relationship of the PTH gene polymorphisms and bone phenotypic variation [17,19,33]. Higher metacarpal diameter and cross-sectional cortical area and a slower decrease in radial cortical area with age were associated with the absence of the BstBI restriction site of the PTH gene in 91 healthy Caucasian women [33]. Association study of the PTH BstBI RFLP with BMD in 383 random healthy postmenopausal women in Japan showed that the subjects with Bb genotype might be in a relatively higher state of bone turnover than those with BB genotype, and the polymorphism in the PTH gene might be a useful genetic marker for prediction of BMD and susceptibility for osteoporosis [17]. The above results from conventional association studies in Japanese females suggest that genetic variation at PTH gene might affect bone metabolism or confer risks for osteoporosis. However, Deng et al. [19] detected no significant results when testing the relationship of the PTH gene’s BstBI marker with hip and spine BMD via TDT in Caucasians [19]. Several reasons might account for the negative findings of the current study. First, the PTH gene’s effects may be more evident in old females as shown in the study by Hosoi et al. [17], where all of the subjects were postmenopausal women. This is supported by the fact that secondary hyperparathyroidism is one of the major mechanisms underlying postmenopausal bone loss [34,35]. Through hyperparathyroidism, the PTH gene’s effects on bone might be magnified on postmenopausal women, making the association between the PTH gene polymorphism with bone phenotypes more significant in old than in young subjects. Therefore it might be difficult for the current study and the study by Deng et al. [19] using young or a mixture of young and old subjects to detect the relationship of the PTH gene and bone mass variation. Interestingly, in the mother group of our subjects, we did find marginally significant association (p ¼ 0:07) between the BstBI polymorphism and Ward’s triangle’s BMD values. The association for other regions is not significant. However, there is a clear trend towards higher BMD values for the BB group as compared to the Bb group for those regions, with the observed mean BMD or BMC values higher for the BB than the Bb subjects. This observation is in agreement with the findings of Hosoi et al. [17] and falls into the pattern that the PTH gene’s association with bone mass variation tends to become more evident after menopause. Second, linkage disequilibrium (LD) generally exists over only a short distance in the genome and TDT findings depend crucially on the LD between the marker and the functional mutations inside a gene. Hence, even if a functional mutation exists in the PTH gene, it is still
possible that the current study could not detect it as the BstBI marker used may be outside the range of the LD with that mutation [19,23,36]. Further association and TDT studies should use denser makers evenly spaced throughout the PTH gene in pursuit of stronger LDs between the markers and functional mutations inside the PTH gene. Third, the less informative RFLP marker and the limited number of sibs (62 sib pairs) used in the current study renders us less information and only modest power in linkage analysis. As a result, a potential linkage between the PTH gene and the bone phenotypes may not be detected. In conclusion, our data do not support the PTH gene as a candidate gene associated with BMD and BMC variation at the spine or hip in Chinese. The negative finding may reflect an age-specific effect of the PTH gene on bone mass regulation. The gene’s effect may be more significant in the postmenopausal period, when hyperparathyroidism represents a major mechanism underlying postmenopausal bone loss. This is the first study testing the PTH gene’s importance to bone phenotypic variation in Chinese. It will contribute to the efforts of gene-mapping for osteoporosis in the Chinese population.
Acknowledgments The study was partially supported by an Honorary Professor Startup Fund from Hunan Province (25000612), an Outstanding Young Scientist Grant from National Science Foundation of China (NSFC) (30025025), a general (30170504) and a key project grant from NSFC, a Seed Fund from the Ministry of Education of China (25000106), a key project grant from the Ministry of Education of China, and a grant from Huo Ying-Dong Education Foundation. Some investigators (H.W.D. and Y.Z.L.) were partially supported by grants from Health Future Foundation of the USA, grants from the National Institute of Health (K01 AR02170-01, R01 GM60402-01 A1), grants from the State of Nebraska Cancer and Smoking Related Disease Research Program (LB595) and the State of Nebraska Tobacco Settlement Fund (LB692), and US Department of Energy grant (DE-FG03-00ER63000/ A00). We thank all the study subjects for volunteering to participate in the study.
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Parathyroid hormone gene with bone phenotypes in Chinese Xiao-Gang Zhou,a Yao-Zhong Liu,b Miao-Xin Li,a Wei-Xia Jian,a Shu-Feng Lei,a Yue-Juan Qin,c Qi Zhou,c and Hong-Wen Denga,b,* a
Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, PR China b Osteoporosis Research Center and Department of Biomedical Sciences, Creighton University Medical Center, 601 N. 30th St., Suite 6787, Omaha, NE 68131, USA c The 6th People’s Hospital of Shanghai, Shanghai 200233, PR China Received 12 June 2003
Abstract Osteoporosis is a common disorder afflicting old people. The parathyroid hormone (PTH) gene is involved in bone remodeling and calcium homeostasis, and has been considered as an important candidate gene for osteoporosis. In this study, we simultaneously tested linkage and/or association of PTH gene with bone mineral density (BMD) and bone mineral content (BMC), two important risk factors for osteoporosis. A sample of 1263 subjects from 402 Chinese nuclear families was used. The families are composed of both parents and at least one healthy daughter aged from 20 to 45 years. All the subjects were genotyped at the polymorphic BstBI site inside the intron 2 of the PTH gene (a nucleotide substitution of G to A at the position +3244). BMD and BMC were measured at the lumbar spine and the hip region via dual-energy X-ray absorptiometry (DXA). Using QTDT (quantitative trait transmission disequilibrium test), we did not find significant results for association or linkage between the PTH gene and BMD or BMC variation at the spine or hip. Our data do not support the PTH gene as a quantitative trait locus (QTL) underlying the bone phenotypic variation in the Chinese population. Ó 2003 Elsevier Inc. All rights reserved. Keywords: Analysis of covariance; Association; Bone mineral content; Bone mineral density; Linkage; The parathyroid hormone gene; Transmission disequilibrium test
Osteoporosis is a common disorder afflicting old people [1,2]. It was estimated that for 60-year-old Caucasian women and men, the risk for an osteoporotic fracture (OF) was 60% and 30%, respectively, for their remaining lifetime [3]. Bone mineral density (BMD) and bone mineral content (BMC) are important risk factors for OFs [4–7]. Extensive studies have been performed in Caucasians to test candidate genes against BMD or BMC variation through traditional association or linkage approaches. Few studies have been done through the contemporary transmission disequilibrium test (TDT), which is robust to population stratification [8]. Parathyroid hormone (PTH) is an 84-amino-acid polypeptide hormone. It has significant effects on bone * Corresponding author. Fax: 1-402-280-5034. E-mail address: [email protected] (H.-W. Deng).
0006-291X/03/$ - see front matter Ó 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0006-291X(03)01261-0
metabolism [9]. Upon PTH binding to its receptor and activation of G proteins, a signal transduction cascade through the cAMP/protein kinase A (PKA) pathway [10], the protein kinase C (PKC) pathway [11], or calcium pathway is initiated that ultimately leads to changes in osteoblastic function [12]. Activation of osteoblasts by PTH results in expression of genes important for the degradation of the extracellular matrix, production of growth factors, and stimulation and recruitment of osteoclasts. The overall effect of PTH is to raise plasma levels of calcium, partly through bone resorption [13]. Studies on mice also showed that PTH plays an important role to stimulate osteoclast formation and bone resorption [14]. The human PTH gene is localized in 11p15.3-p15.1 [15]. The nucleotide substitutions of G to A at the position +3244 is defined by the BstBI restriction fragment length polymorphism (RFLP) inside the PTH gene [16].
X.-G. Zhou et al. / Biochemical and Biophysical Research Communications 307 (2003) 666–671
The PTH gene has been considered as an important candidate gene for osteoporosis. Yet only a few studies have been performed on the relationship of the PTH gene polymorphism and bone mass variation [17–20]. In Chinese, there has been no such study reported on the relationship of PTH gene and bone mass variation. Three approaches have been employed to identify genes underlying complex trait variation: association, linkage, and TDT analysis. The finding of an association only represents a tentative evidence that a marker is linked to a disease gene, since population stratification may give rise to spurious association [21]. The linkage study has limited statistical power when employed to a complex trait [22,23]. As a result, linkage findings are difficult to replicate across studies [24]. The TDT is a family-based test of association and widely used to search for the genetic factors in diseases. It compares alleles transmitted vs. those non-transmitted from parents to affected offspring. It is robust to population stratification that can easily lead to spurious association [25]. Provided that an association is present, the TDT often has more power than conventional linkage tests [22,23,25,26]. Given the potential importance of PTH in bone remodeling and calcium homeostasis, we use the conventional linkage and association (total-family association and analysis of covariance) approaches as well as the more contemporary TDT (within-family association) approach [8] to test the PTH gene as a quantitative trait locus (QTL) underlying the bone phenotypic variation (BMD and BMC) in the Chinese population.
Materials and methods Subjects. The study was approved by the Research Administration Departments of Hunan Normal University and the 6th People’s Hospital of Shanghai, PR China. We have recruited 1263 subjects from 402 nuclear families with both parents and at least one healthy daughter (whose ages range from 20 to 45). All the study subjects belong to the Chinese Han ethnic group. The nuclear families vary in size from 3 to 6 individuals, with a mean of 3.14 individuals. The numbers of families with one daughter, two daughters, three daughters, and four daughters are 350, 48, 3, and 1, respectively. All the subjects were recruited by the 6th People’s Hospital of Shanghai from a local population of the City of Shanghai located on the Mid-East Coast of PR China, and signed informed-consent documents before entering the project. We adopted the exclusion criteria defined in detail by Deng et al. [19] for daughters to minimize any known potential confounding effects on the bone phenotypes. PCR-RFLP. Genomic DNA was isolated according to the phenol–chloroform extraction protocols [27]. Genomic DNA (0.1–0.3 lg) was amplified in 25 ll of buffer solution (10 mM Tris–HCl [pH 9.0], 50 mM KCl, 0.1% Triton X-100, 0.9 mM MgCl2 , and 240 lM each of four deoxyribonucleotides). One unit of Taq polymerase (Sangon, Shanghai, PR China) and 0.52 lM each of oligonucleotide primer (the forward in intron 1: 50 -CAT TCT GTG TAC TAT AGT TTG30 , the reverse in the 30 flank region: 50 -GAG CTT TGA ATT AGC AGC ATG-30 ) were used in the reaction to generate a DNA fragment of 600 bp with BstBI RFLP inside the intron 2 of the PTH gene.
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Polymerase chain reaction (PCR) was performed in 38 cycles as follows: denaturation at 95 °C for 30 s, annealing at 50 °C for 30 s, and extension at 72 °C for 60 s on a PE9700 Thermal Cycler (Perkin Elmer Cetus, Norwalk, CT). After amplification, the PCR product was digested with restriction endonuclease BstBI (NEB Biotech., England) for 4 h at 65 °C and electrophoresed in a 2% agarose gel (Shanghai Yito Enterprise, Shanghai, PR China), stained by ethidium bromide, and then visualized under UV light. The RFLP polymorphisms of PTH BstBI were represented as B and b (B: 387 + 213 bp; b: 600 bp) [28]. Measurement. BMD (g/cm2 ) and BMC (g) of the spine (L1–L4), femoral neck, trochanter, intertrochanteric region, Ward’s triangle, and total hip (including femoral neck, trochanter, and intertrochanteric region) were measured by a Hologic QDR 2000+ dual-energy Xray absorptiometry (DXA) scanner (Hologic, Waltham MA). The scanner was calibrated daily, and the coefficient of variability (CV) values, which were obtained from seven individuals repeatedly measured for five times, of the DXA measurement at the spine (L1–L4), femoral neck, trochanter, intertrochanteric region, Ward’s triangle, and total hip, were 0.9%, 1.93%, 1.48%, 1.31%, 3.58%, and 0.8%, respectively, for BMD, and 1.32%, 2.59%, 4.74%, 2.45%, 4.51%, and 1.61%, respectively, for BMC. Weight and height were obtained at the same visit when the bone mass was measured. ANCOVA and other regular statistical analyses. Regular statistical analyses were conducted using the SAS program (SAS Institute, Cary, NC, USA). Association of the BstBI polymorphism with bone phenotypes in the mother group was tested with ANCOVA analysis (analysis of covariance). The Hardy–Weinberg distribution of the BstBI marker genotypes was tested with v2 test. Homogeneity of variance and fitted distribution of normal test of BMD and BMC within each of the three PTH BstBI genotypes among fathers, mothers, and daughters were performed with Bartlett’s test and Shapiro–Wilks W test, respectively. The phenotypic values of the trochanter BMD, Ward’s triangle BMD, spine BMC, and Ward’s triangle BMC were logarithm transformed because of the significant violation of normal distribution of these raw values. QTDT analyses. Tests of stratification, within-family association (TDT), total-family association, and linkage between BstBI RFLP and bone mass phenotypes (BMD and BMC) of the above-mentioned six skeletal sites were performed with the program QTDT (quantitative trait transmission disequilibrium test), which is available at the web site (http://www.well.ox.ac.uk/asthma/QTDT). According to Abecasis et al. [29], association can be partitioned into orthogonal between-family (b) and within-family (w) components. The former was sensitive to population structure and the latter was significant only in the presence of linkage disequilibrium and linkage. Since the test of total association evaluates association at population level on all the subjects by using all information including within- and between-family components, it may produce misleading results in the case of population stratification. Linkage analysis in the QTDT is based on the identity-by-descent (IBD) relationship of genotypes among sib pairs and the variance component framework using the likelihood ratio test. The QTDT provides the test of population stratification by evaluating whether the between-family (b) component is equal to within-family association (w) component [29]. Population stratification may only have impact on the between- but not within-family-component estimation [29]. Age, weight, and height are considered as covariates that may have significant effects on the bone phenotypic variation [30]. We used them to adjust for the raw bone phenotypic values before we performed the linkage and/or association tests in order to improve the statistical power by decreasing the effects of the random environmental factors on phenotypic variation and increasing the genetic signal to noise ratio (i.e., h2 estimate) [30]. Since all the offspring were females in the nuclear families, and the effects of parents’ phenotypes were excluded in the QTDT, the sex was not considered as covariates to adjust for the daughters’ bone phenotypes.
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Results The basic characteristics of the study subjects These data are shown in Table 1. There were 769 parents and 459 daughters included. Thirty-five parental bone phenotypic values were not obtained; therefore the number of parents with phenotypes (n ¼ 769) was less than that of parent with genotypes (n ¼ 804). The ages of parents and daughters are 60.8 6.8 years and 31.4 5.8 years (mean SD), respectively. The genotypes and allele frequencies Initially 804 parents and 459 daughters were used for genotyping. Three daughters’ genotypes failed to pass the Mendelian inheritance check within nuclear families. Four daughters’ samples were not amplified in PCR
after three repeated experiments due to the poor quality of DNA. Table 2 shows the data of 804 parents in our sample. The genotype frequencies within the parent group for the BB, Bb, and bb subjects are 73.5%, 24.8%, and 1.7%, respectively. The distribution of the genotypes (within parents) does not deviate from Hardy–Weinberg distribution (p ¼ 0:55). In Table 2, we also show the genotypes and the allele frequencies detected by two other studies. In Japanese postmenopausal women, the frequencies for BB, Bb, and bb are 82.5%, 16.7%, and 0.8%, respectively [17]. In the Caucasians of European origin, the corresponding data are 17%, 54%, and 29% [19], respectively. Our genotypes and allele frequencies in Chinese are a little different from those of Japanese and depart more drastically from that of Caucasians (v2 test, p < 0:001). It indicates that the genotype and allele frequency distribution for the PTH gene BstBI marker might be specific to different ethnic backgrounds. ANCOVA analyses
Table 1 Basic characteristics of parents and daughters Parents (n ¼ 769)
Daughters (n ¼ 459)
Age (year) Height (cm) Weight (kg)
60.8 6.8 160.4 8.2 63.9 10.4
31.4 5.8 159.9 5.2 55.1 8.0
BMD (g/cm2 ) Spine Femoral neck Trochanter Intertrochanter region Ward’s triangle Total hip
0.872 0.161 0.714 0.124 0.597 0.116 0.953 0.170 0.530 0.150 0.812 0.143
0.960 0.100 0.776 0.100 0.637 0.089 0.998 0.130 0.711 0.130 0.855 0.110
BMC (g) Spine Femoral neck Trochanter Intertrochanter region Ward’s triangle Total hip
52.258 14.381 3.663 0.772 6.651 1.945 20.029 5.908 0.612 0.194 30.343 8.218
55.451 8.770 3.695 0.530 6.101 1.170 17.460 3.280 0.867 0.180 27.256 4.440
Note. The BMD and BMC values (means SD) are raw values at the spine or hip.
The phenotype distribution (mean SD) among each genotype of the mother group is displayed in Table 3. As the number of bb subjects is too small (only 5) in our samples, we compared only BB and Bb subjects here. The BMD and BMC values are adjusted with age, weight, and height. Using the ANCOVA, marginal significant genotype–phenotype association (p ¼ 0:07) was detected in the mother group for the Ward’s triangle BMD. The association is not significant for other regions. However, there is a clear trend in these regions that the BB subjects tend to have higher BMD or BMC values than the Bb subjects. The observed mean BMD or BMC values in all the regions examined for the BB group are higher than those for the Bb group. QTDT analyses In QTDT analyses, three nuclear families were excluded in the final analyses because their daughters’ genotypes failed to pass the Mendelian inheritance
Table 2 Allele and genotype frequency distributions in Chinese, Japanese, and Caucasians Chinese (804)
Japanese (383)
Caucasians (620)
Allele frequencies
B ¼ 0:859 b ¼ 0:141
B ¼ 0:909 b ¼ 0:091
B ¼ 0:440 b ¼ 0:560
Genotype frequencies
BB ¼ 0:735 Bb ¼ 0:248 bb ¼ 0:017
BB ¼ 0:825 Bb ¼ 0:167 bb ¼ 0:008
BB ¼ 0:170 Bb ¼ 0:540 bb ¼ 0:290
p ¼ 0:55
p ¼ 0:92
p ¼ 0:03
p value of H.-W. test
2
p value
p < 0:001
Note. Hardy–Weinberg ratio is tested with v test. The data within the parentheses are the number of the study subjects. In the second column, all of the 804 parents in our samples are genotyped and corresponding data are shown here. In the fifth column, the p value shows significant difference (v2 test, p < 0:001) in genotype frequency distribution observed among the Chinese, Japanese, and the Caucasians. The data for the Japanese are cited from Hosoi et al. [17]. The data for the Caucasians are cited from Deng et al. [19].
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Table 3 ANCOVA test of bone phenotypes of the mother group p values
Genotype BB (n ¼ 293)
Bb (n ¼ 83)
2
BMD (g/cm ) Spine Femoral neck Trochanter Intertrochanter region Ward’s triangle Total hip
0.817 0.120 0.682 0.103 0.549 0.086 0.886 0.125 0.514 0.130 0.754 0.103
0.804 0.128 0.662 0.096 0.534 0.086 0.865 0.122 0.485 0.130 0.736 0.103
0.43 0.10 0.16 0.19 0.07 0.18
BMC (g) Spine Femoral neck Trochanter Intertrochanter region Ward’s triangle Total hip
44.514 9.159 3.248 0.454 5.378 0.993 15.986 2.763 0.599 0.171 24.612 3.722
43.449 9.171 3.177 0.455 5.248 0.994 15.914 2.768 0.567 0.172 24.339 3.728
0.35 0.21 0.30 0.84 0.13 0.56
Note. The BMD and BMC (means SD) values are adjusted by age, weight, and height. Mothers with bb genotypes are excluded here because the number of them is only five in our sample. Significance level is set at p < 0:05.
check. The genotypic values of the four daughters, whose samples were not amplified in PCR, were coded as zero (0). Thirty-five missing parental bone phenotypic values were coded as an unusual number (i.e., -x99.999). Because the effects of the parental phenotypes were excluded in the analyses, these missing values have no effect on our results. Therefore, 399 families with 1254 individuals are included here. The phenotypes used for linkage and TDT analyses are those of daughters. Using the QTDT program, we did not detect any significant population stratification in our samples, and found no significant association (including within-family association and total-family association) or linkage between the PTH BstBI marker polymorphism and the bone mass variation at the spine and the hip (Table 4).
Discussion BMD and BMC have been regarded as important determinants of OFs [6,7,31,32]. In recent years, extensive efforts have been made to find and confirm genes or genomic regions underlying BMD and BMC variation by applying linkage or association approaches in Caucasians [7,19,32]. However, few such studies have been conducted in Chinese population. In this study, using a more contemporary statistical method, TDT, we studied the PTH gene as a candidate gene underlying BMD and BMC variation at the spine and hip in 402 Chinese nuclear families. After adjusting for the covariates of age, height, and weight, we did not find significant association between the PTH BstBI polymorphisms and BMD/BMC variation at the spine or hip.
Table 4 Results of tests of population stratification, within-family association, total-family association, and linkage Test of population stratification
Test of within-family association
Test of total-family association
Test of linkage
BMD Spine emoral neck Trochanter Intertrochanter Ward’s triangle Total hip
0.05 0.69 0.81 0.58 0.81 0.68
1.00 0.20 0.57 0.51 0.16 0.41
1.00 1.00 1.00 1.00 1.00 1.00
0.73 1.00 1.00 1.00 0.78 1.00
BMC Spine Femoral neck Trochanter Intertrochanter Ward’s triangle Total hip
0.92 0.48 0.68 0.45 0.33 0.37
1.00 0.26 0.84 0.65 0.44 0.70
1.00 1.00 1.00 1.00 1.00 1.00
0.49 1.00 0.61 1.00 0.38 0.46
Note. All the tests are conducted by employing the program QTDT. The phenotypic values are adjusted for significant covariates of age, height, and weight. Values presented are the p values of given v2 tests.
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PTH plays an important role in bone remodeling and calcium homeostasis. Several polymorphisms (e.g., DraII, NlaIV, BstBI, and TaqI polymorphisms) have been identified inside the PTH gene [28]. A few studies have been performed on the relationship of the PTH gene polymorphisms and bone phenotypic variation [17,19,33]. Higher metacarpal diameter and cross-sectional cortical area and a slower decrease in radial cortical area with age were associated with the absence of the BstBI restriction site of the PTH gene in 91 healthy Caucasian women [33]. Association study of the PTH BstBI RFLP with BMD in 383 random healthy postmenopausal women in Japan showed that the subjects with Bb genotype might be in a relatively higher state of bone turnover than those with BB genotype, and the polymorphism in the PTH gene might be a useful genetic marker for prediction of BMD and susceptibility for osteoporosis [17]. The above results from conventional association studies in Japanese females suggest that genetic variation at PTH gene might affect bone metabolism or confer risks for osteoporosis. However, Deng et al. [19] detected no significant results when testing the relationship of the PTH gene’s BstBI marker with hip and spine BMD via TDT in Caucasians [19]. Several reasons might account for the negative findings of the current study. First, the PTH gene’s effects may be more evident in old females as shown in the study by Hosoi et al. [17], where all of the subjects were postmenopausal women. This is supported by the fact that secondary hyperparathyroidism is one of the major mechanisms underlying postmenopausal bone loss [34,35]. Through hyperparathyroidism, the PTH gene’s effects on bone might be magnified on postmenopausal women, making the association between the PTH gene polymorphism with bone phenotypes more significant in old than in young subjects. Therefore it might be difficult for the current study and the study by Deng et al. [19] using young or a mixture of young and old subjects to detect the relationship of the PTH gene and bone mass variation. Interestingly, in the mother group of our subjects, we did find marginally significant association (p ¼ 0:07) between the BstBI polymorphism and Ward’s triangle’s BMD values. The association for other regions is not significant. However, there is a clear trend towards higher BMD values for the BB group as compared to the Bb group for those regions, with the observed mean BMD or BMC values higher for the BB than the Bb subjects. This observation is in agreement with the findings of Hosoi et al. [17] and falls into the pattern that the PTH gene’s association with bone mass variation tends to become more evident after menopause. Second, linkage disequilibrium (LD) generally exists over only a short distance in the genome and TDT findings depend crucially on the LD between the marker and the functional mutations inside a gene. Hence, even if a functional mutation exists in the PTH gene, it is still
possible that the current study could not detect it as the BstBI marker used may be outside the range of the LD with that mutation [19,23,36]. Further association and TDT studies should use denser makers evenly spaced throughout the PTH gene in pursuit of stronger LDs between the markers and functional mutations inside the PTH gene. Third, the less informative RFLP marker and the limited number of sibs (62 sib pairs) used in the current study renders us less information and only modest power in linkage analysis. As a result, a potential linkage between the PTH gene and the bone phenotypes may not be detected. In conclusion, our data do not support the PTH gene as a candidate gene associated with BMD and BMC variation at the spine or hip in Chinese. The negative finding may reflect an age-specific effect of the PTH gene on bone mass regulation. The gene’s effect may be more significant in the postmenopausal period, when hyperparathyroidism represents a major mechanism underlying postmenopausal bone loss. This is the first study testing the PTH gene’s importance to bone phenotypic variation in Chinese. It will contribute to the efforts of gene-mapping for osteoporosis in the Chinese population.
Acknowledgments The study was partially supported by an Honorary Professor Startup Fund from Hunan Province (25000612), an Outstanding Young Scientist Grant from National Science Foundation of China (NSFC) (30025025), a general (30170504) and a key project grant from NSFC, a Seed Fund from the Ministry of Education of China (25000106), a key project grant from the Ministry of Education of China, and a grant from Huo Ying-Dong Education Foundation. Some investigators (H.W.D. and Y.Z.L.) were partially supported by grants from Health Future Foundation of the USA, grants from the National Institute of Health (K01 AR02170-01, R01 GM60402-01 A1), grants from the State of Nebraska Cancer and Smoking Related Disease Research Program (LB595) and the State of Nebraska Tobacco Settlement Fund (LB692), and US Department of Energy grant (DE-FG03-00ER63000/ A00). We thank all the study subjects for volunteering to participate in the study.
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