[Analysis of flavonoids and antitumor activity of transgenic Saussurea involucrate].

The aim of this paper was to investigate the flavonoids of callus of transgenic and non-transgenic Saussurea involucrate and its antitumor activity on the esophageal cancer CaEs-17 cells. The species and content of mono-phenols were detected by high performance liquid chromatography. The growth of human esophageal cancer CaEs-17 cells was detected using CCK-8 assay, apoptosis morphology observation and flow cytometry. Expression of related apoptotic genes Bax and Bcl-2 were determined by qPCR. The results showed that the content of total flavonoids in the transgenic callus was 2.72 times that of the non-transgenic callus. The cyanidin-galactoside was detected in the transgenic callus, but not in the non-transgenic callus. The inhibitory effect of the extracts from the transgenic callus on CaEs-17 cells was more significant than that of the non-transgenic callus, and the IC50 value had a decreased of 26.4%. Flow cytometry analysis results showed that the apoptosis induction effect of the extracts from the transgenic callus on CaEs-17 cells was significantly better than that of the non-transgenic callus. Fluorescence quantitative PCR analysis results showed that the extracts from the transgenic callus could up-regulate the expression of proapoptotic gene Bax and down-regulate the expression of apoptotic gene Bcl-2, and the regulation effect of the transgenic callus was more significant. Therefore, compared with the non-transgenic callus, the antitumor activity of the extracts from the callus of transgenic S. involucrate on the esophageal cancer CaEs-17 cells was significantly increased, which was closely related to the accumulation of cyanidin-galactoside and its metabolism-related flavonoid compounds in the transgenic callus.

Small extrachromosomal circular DNA harboring targeted tumor suppressor gene mutations supports intratumor heterogeneity in mouse liver cancer induced by multiplexed CRISPR/Cas9.

BACKGROUND: Primary liver cancer has significant intratumor genetic heterogeneity (IGH), which drives cancer evolution and prevents effective cancer treatment. CRISPR/Cas9-induced mouse liver cancer models can be used to elucidate how IGH is developed. However, as CRISPR/Cas9 could induce chromothripsis and extrachromosomal DNA in cells in addition to targeted mutations, we wondered whether this effect contributes to the development of IGH in CRISPR/Cas9-induced mouse liver cancer. METHODS: CRISPR/Cas9-based targeted somatic multiplex-mutagenesis was used to target 34 tumor suppressor genes (TSGs) for induction of primary liver tumors in mice. Target site mutations in tumor cells were analyzed and compared between single-cell clones and their subclones, between different time points of cell proliferation, and between parental clones and single-cell clones derived from mouse subcutaneous allografts. Genomic instability and generation of extrachromosomal circular DNA (eccDNA) was explored as a potential mechanism underlying the oscillation of target site mutations in these liver tumor cells. RESULTS: After efficiently inducing autochthonous liver tumors in mice within 30-60 days, analyses of CRISPR/Cas9-induced tumors and single-cell clones derived from tumor nodules revealed multiplexed and heterogeneous mutations at target sites. Many target sites frequently displayed more than two types of allelic variations with varying frequencies in single-cell clones, indicating increased copy number of these target sites. The types and frequencies of targeted TSG mutations continued to change at some target sites between single-cell clones and their subclones. Even the proliferation of a subclone in cell culture and in mouse subcutaneous graft altered the types and frequencies of targeted TSG mutations in the absence of continuing CRISPR/Cas9 genome editing, indicating a new source outside primary chromosomes for the development of IGH in these liver tumors. Karyotyping of tumor cells revealed genomic instability in these cells manifested by high levels of micronuclei and chromosomal aberrations including chromosomal fragments and chromosomal breaks. Sequencing analysis further demonstrated the generation of eccDNA harboring targeted TSG mutations in these tumor cells. CONCLUSIONS: Small eccDNAs carrying TSG mutations may serve as an important source supporting intratumor heterogeneity and tumor evolution in mouse liver cancer induced by multiplexed CRISPR/Cas9.

MicroRNA profiling and prediction of recurrence/relapse-free survival in stage I lung cancer.

About 30% stage I non-small cell lung cancer (NSCLC) patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. MicroRNAs (miRNAs) are a class of small non-coding RNAs of 19-25 nt and play important roles in gene regulation in human cancers. The purpose of this study is to identify miRNA expression profiles that would better predict prognosis of stage I NSCLC. MiRNAs extracted from 527 stage I NSCLC patients were profiled on the human miRNA expression profiling v2 panel (Illumina). The expression profiles were analyzed for their association with cancer subtypes, lung cancer brain metastasis and recurrence/relapse free survival (RFS). MiRNA expression patterns between lung adenocarcinoma and squamous cell carcinoma differed significantly with 171 miRNAs, including Let-7 family members and miR-205. Ten miRNAs associated with brain metastasis were identified including miR-145*, which inhibit cell invasion and metastasis. Two miRNA signatures that are highly predictive of RFS were identified. The first contained 34 miRNAs derived from 357 stage I NSCLC patients independent of cancer subtype, whereas the second containing 27 miRNAs was adenocarcinoma specific. Both signatures were validated using formalin-fixed paraffin embedded and/or fresh frozen tissues in independent data set with 170 stage I patients. Our findings have important prognostic or therapeutic implications for the management of stage I lung cancer patients. The identified miRNAs hold great potential as targets for histology-specific treatment or prevention and treatment of recurrent disease.

Evidence for major pleiotropic effects on bone size variation from a principal component analysis of 451 Caucasian families.

AIM: To identify pleiotropic quantitative trait loci (QTL) influencing bone size (BS) at different skeletal sites in Caucasians. METHODS: In a sample containing 3899 Caucasians from 451 pedigrees, 410 microsatellite markers spaced approximately 8.9 cM apart across the human genome were genotyped. Phenotypical and genetic correlations of BS at lumbar spine, hip (femoral neck, trochanter, and intertrochanter regions), and wrist (ultradistal, mid-distal, and one-third distal sites) were determined using bivariate quantitative genetic analysis. A principal component analysis (PCA) was performed to obtain principal component (PC) factors that were then subjected to variance components linkage analysis to identify regions linked to the PC. RESULTS: Genetic correlations of BS at different skeletal sites ranged from 0.40 to 0.79 (P<0.001). The PCA yielded a PC named PCtotal, which explained up to 76% of the total (co)variation of all the BS at the 7 skeletal sites for the whole sample. We identified a QTL influencing the BS of multiple skeletal sites on chromosome 7 at 140 cM [logarithm of odds (LOD)=2.85] in the overall sample. Sex-specific evidence for linkage was observed on chromosome 11 at 53 cM (LOD =2.82) in the male-only data subset. CONCLUSION: Our study identified several genomic regions that may have pleiotropic effects on different skeletal sites. These regions may contain genes that play a critical role in overall bone development and osteoporosis at multiple skeletal sites, hence are biologically and clinically important.

Bivariate whole genome linkage analysis for femoral neck geometric parameters and total body lean mass.

UNLABELLED: A genome-wide bivariate analysis was conducted for femoral neck GPs and TBLM in a large white sample. We found QTLs shared by GPs and TBLM in the total sample and the sex-specific samples. QTLs with potential pleiotropy were also disclosed. INTRODUCTION: Previous studies have suggested that femoral neck cross-section geometric parameters (FNCS-GPs), including periosteal diameter (W), cross-sectional area (CSA), cortical thickness (CT), buckling ratio (BR), and section modulus (Z), are genetically correlated with total body lean mass (TBLM). However, the shared genetic factors between them are unknown. MATERIALS AND METHODS: To identify the specific QTLs shared by FNCS-GPs and TBLM, we performed bivariate whole genome linkage analysis (WGLA) in a large sample of 451 white families made up of 4498 subjects. RESULTS: Multipoint bivariate linkage analyses for 22 autosomes showed evidence of suggestive or significant linkages (thresholds of LOD = 2.3 and 3.7, respectively) to chromosomes 3q12 and 20q13 in the entire sample, 6p25 and 10q24 in women, and 4p15, 5q34-35 and 7q21 in men. Two-point linkage analyses for chromosome X showed strong linkage to Xp22.13, Xp11.4, Xq22.3, Xq23-24, and Xq25. Complete pleiotropy was identified on 10q24 and 5q35 for TBLM and BR in women and for TBLM and CT in men, respectively. Furthermore, chromosomes 5q34-35, 7q21, 10q24, 20q13, Xp22.13, Xp11.4, and Xq25 are also of importance because of their linkage to multiple trait pairs. For example, linkage to chromosome 10q24 was found for TBLM x W (LOD = 2.31), TBLM x CT (LOD = 2.51), TBLM x CSA (LOD = 2.51), TBLM x BR (LOD = 2.64), and TBLM x Z (LOD = 2.55) in women. CONCLUSIONS: In this study, we identified several genomic regions (e.g., 3q12 and 20q13) that seem to be linked to both FNCS-GPs and TBLM. These regions are of interesting because they may harbor genes that may contribute to variation in both FNCS-GPs and TBLM.

Relationship of obesity with osteoporosis.

CONTEXT: The relationship between obesity and osteoporosis has been widely studied, and epidemiological evidence shows that obesity is correlated with increased bone mass. Previous analyses, however, did not control for the mechanical loading effects of total body weight on bone mass and may have generated a confounded or even biased relationship between obesity and osteoporosis. OBJECTIVE: The objective of this study was to reevaluate the relationship between obesity and osteoporosis by accounting for the mechanical loading effects of total body weight on bone mass. METHODS: We measured whole body fat mass, lean mass, percentage fat mass, body mass index, and bone mass in two large samples of different ethnicity: 1988 unrelated Chinese subjects and 4489 Caucasian subjects from 512 pedigrees. We first evaluated the Pearson correlations among different phenotypes. We then dissected the phenotypic correlations into genetic and environmental components with bone mass unadjusted or adjusted for body weight. This allowed us to compare the results with and without controlling for mechanical loading effects of body weight on bone mass. RESULTS: In both Chinese and Caucasian subjects, when the mechanical loading effect of body weight on bone mass was adjusted for, the phenotypic correlation (including its genetic and environmental components) between fat mass (or percentage fat mass) and bone mass was negative. Further multivariate analyses in subjects stratified by body weight confirmed the inverse relationship between bone mass and fat mass, after mechanical loading effects due to total body weight were controlled. CONCLUSIONS: Increasing fat mass may not have a beneficial effect on bone mass.

Accurate haplotype inference for multiple linked single-nucleotide polymorphisms using sibship data.

Sibships are commonly used in genetic dissection of complex diseases, particularly for late-onset diseases. Haplotype-based association studies have been advocated as powerful tools for fine mapping and positional cloning of complex disease genes. Existing methods for haplotype inference using data from relatives were originally developed for pedigree data. In this study, we proposed a new statistical method for haplotype inference for multiple tightly linked single-nucleotide polymorphisms (SNPs), which is tailored for extensively accumulated sibship data. This new method was implemented via an expectation-maximization (EM) algorithm without the usual assumption of linkage equilibrium among markers. Our EM algorithm does not incur extra computational burden for haplotype inference using sibship data when compared with using unrelated parental data. Furthermore, its computational efficiency is not affected by increasing sibship size. We examined the robustness and statistical performance of our new method in simulated data created from an empirical haplotype data set of human growth hormone gene 1. The utility of our method was illustrated with an application to the analyses of haplotypes of three candidate genes for osteoporosis.

Improvement of mapping accuracy by unifying linkage and association analysis.

It is well known that pedigree/family data record information on the coexistence in founder haplotypes of alleles at nearby loci and the cotransmission from parent to offspring that reveal different, but complementary, profiles of the genetic architecture. Either conventional linkage analysis that assumes linkage equilibrium or family-based association tests (FBATs) capture only partial information, leading to inefficiency. For example, FBATs will fail to detect even very tight linkage in the case where no allelic association exists, while a violation of the assumption of linkage equilibrium will result in biased estimation and reduced efficiency in linkage mapping. In this article, by using a data augmentation technique and the EM algorithm, we propose a likelihood-based approach that embeds both linkage and association analyses into a unified framework for general pedigree data. Relative to either linkage or association analysis, the proposed approach is expected to have greater estimation accuracy and power. Monte Carlo simulations support our theoretical expectations and demonstrate that our new methodology: (1) is more powerful than either FBATs or classic linkage analysis; (2) can unbiasedly estimate genetic parameters regardless of whether association exists, thus remedying the bias and less precision of traditional linkage analysis in the presence of association; and (3) is capable of identifying tight linkage alone. The new approach also holds the theoretical advantage that it can extract statistical information to the maximum extent and thereby improve mapping accuracy and power because it integrates multilocus population-based association study and pedigree-based linkage analysis into a coherent framework. Furthermore, our method is numerically stable and computationally efficient, as compared to existing parametric methods that use the simplex algorithm or Newton-type methods to maximize high-order multidimensional likelihood functions, and also offers the computation of Fisher's information matrix. Finally, we apply our methodology to a genetic study on bone mineral density (BMD) for the vitamin D receptor (VDR) gene and find that VDR is significantly linked to BMD at the one-third region of the wrist.

A gene expression signature predicts survival of patients with stage I non-small cell lung cancer.

BACKGROUND: Lung cancer is the leading cause of cancer-related death in the United States. Nearly 50% of patients with stages I and II non-small cell lung cancer (NSCLC) will die from recurrent disease despite surgical resection. No reliable clinical or molecular predictors are currently available for identifying those at high risk for developing recurrent disease. As a consequence, it is not possible to select those high-risk patients for more aggressive therapies and assign less aggressive treatments to patients at low risk for recurrence. METHODS AND FINDINGS: In this study, we applied a meta-analysis of datasets from seven different microarray studies on NSCLC for differentially expressed genes related to survival time (under 2 y and over 5 y). A consensus set of 4,905 genes from these studies was selected, and systematic bias adjustment in the datasets was performed by distance-weighted discrimination (DWD). We identified a gene expression signature consisting of 64 genes that is highly predictive of which stage I lung cancer patients may benefit from more aggressive therapy. Kaplan-Meier analysis of the overall survival of stage I NSCLC patients with the 64-gene expression signature demonstrated that the high- and low-risk groups are significantly different in their overall survival. Of the 64 genes, 11 are related to cancer metastasis (APC, CDH8, IL8RB, LY6D, PCDHGA12, DSP, NID, ENPP2, CCR2, CASP8, and CASP10) and eight are involved in apoptosis (CASP8, CASP10, PIK3R1, BCL2, SON, INHA, PSEN1, and BIK). CONCLUSIONS: Our results indicate that gene expression signatures from several datasets can be reconciled. The resulting signature is useful in predicting survival of stage I NSCLC and might be useful in informing treatment decisions.

Predictive factors for age at menopause in Caucasian females.

OBJECTIVE: Early onset of menopause results in the premature exposure to low estrogen levels and is associated with a number of postmenopausal health problems and higher risk of mortality. The aim of this study was to determine genetic and environmental factors associated with age at natural and surgical menopause. METHODS: Multiple regression analysis using a sample of Caucasians composed of 154 females with surgical and 248 with natural menopause. RESULTS: Breastfeeding is a significant predictor of earlier natural menopause (P<0.05). Use of oral contraceptives and smoking were not significantly associated with age at menopause. Females who did not have history of pregnancies are at significantly higher risk (P<0.001) of getting early surgical menopause than those who did. We also tested the association of seven single nucleotide polymorphisms (SNPs) of the estrogen receptor alpha (ER-alpha) gene with age at menopause. No association was observed with age at menopause but the PvuII p allele was overrepresented in women with surgical menopause and associated with menopause per se (P=0.029; OR=1.8, 95% CI=1.1-3.0). CONCLUSIONS: Breastfeeding and alcohol consumption are significantly associated with earlier natural menopause. No significant effects of the ER-alpha genotypes were observed on the age of menopause. Given the important role of the ER-alpha in estrogen signaling, which directly influences the menopausal process, further studies are required to better define the relationship between this gene and age at menopause.

Impacts of QTL x environment interactions on genetic response to marker-assisted selection.

Genotype x environment (GE) interaction is a common characteristic for quantitative traits, and has been a subject of great concern for breeding programs. Simulation studies were conducted to investigate the effects of GE interaction on genetic response to marker-assisted selection (MAS). In our study we demonstrated that MAS is generally more efficient than phenotypic selection in the presence of GE interaction, and this trend is more pronounced for developing broadly adaptable varieties. The utilization of different QTL information dramatically influences MAS efficiency. When MAS is based on QTLs evaluated in a single environment, the causal QTL x environment (QE) interactions usually reduce general response across environments, and the reduction in the cumulative general response is a function of the proportion of QE interactions for the trait studied. However, MAS using QTL information evaluated in multiple environments not only yields higher general response, but the general response obtained is also reasonably robust to QE interactions. The total response achieved by MAS in a specific environment depends largely on the total heritability of traits and is slightly subject to relative changes between general heritability and GE interaction heritability. Two breeding strategies, breeding experiments conducted in one environment throughout and in two environments alternately, were also examined for the implementation of marker-based selection. It was thus concluded that plant breeders should be cautious to utilize QTL information from only one environment and execute breeding studies in another.

Mapping quantitative trait loci for cross-sectional geometry at the femoral neck.

UNLABELLED: A genome-wide linkage scan was performed in a sample of 79 multiplex pedigrees to identify genomic regions linked to femoral neck cross-sectional geometry. Potential quantitative trait loci were detected at several genomic regions, such as 10q26, 20p12-q12, and chromosome X. INTRODUCTION: Bone geometry is an important determinant of bone strength and osteoporotic fractures. Previous studies have shown that femoral neck cross-sectional geometric variables are under genetic controls. To identify genetic loci underlying variation in femoral neck cross-sectional geometry, we conducted a whole genome linkage scan for four femoral neck cross-sectional geometric variables in 79 multiplex white pedigrees. MATERIALS AND METHODS: A total of 1816 subjects from 79 pedigrees were genotyped with 451 microsatellite markers across the human genome. We performed linkage analyses on the entire data, as well as on men and women separately. RESULTS: Significant linkage evidence was identified at 10q26 for buckling ratio (LOD = 3.27) and Xp11 (LOD = 3.45) for cortical thickness. Chromosome region 20p12-q12 showed suggestive linkage with cross-sectional area (LOD = 2.33), cortical thickness (LOD = 2.09), and buckling ratio (LOD = 1.94). Sex-specific linkage analyses further supported the importance of 20p12-q12 for cortical thickness (LOD = 2.74 in females and LOD = 1.88 in males) and buckling ratio (LOD = 5.00 in females and LOD = 3.18 in males). CONCLUSIONS: This study is the first genome-wide linkage scan searching for quantitative trait loci underlying femoral neck cross-sectional geometry in humans. The identification of the genes responsible for bone geometric variation will improve our knowledge of bone strength and aid in development of diagnostic approaches and interventions for osteoporotic fractures.

Linkage and association analyses of the UCP3 gene with obesity phenotypes in Caucasian families.

Uncoupling protein 3 (UCP3) uncouples ATP production from mitochondrial respiration, thereby dissipating energy as heat and affecting the efficiency of energy metabolism. Genetic variations in the UCP3 gene have been conceived to affect body weight in the general population. In this study, using the quantitative transmission disequilibrium test (QTDT), we assessed linkage and association between the UCP3 gene and obesity phenotypes in a large sample of 1,873 subjects from 405 United States Caucasian nuclear families. Obesity phenotypes tested include body mass index (BMI), fat mass, percent fat mass (PFM), and lean mass, with the latter three measured by dual-energy X-ray absorptiometry. We first selected five single nucleotide polymorphisms (SNPs) and then analyzed three highly polymorphic ones, namely, -55 C/T (promoter), Tyr99Tyr (exon 3), and Tyr210Tyr (exon 5), in the total sample. Significant linkage disequilibria (0.392

Quantifying the relationship between gene expressions and trait values in general pedigrees.

Treating mRNA transcript abundances as quantitative traits and examining their relationships with clinical traits have been pursued by using an analytical approach of quantitative genetics. Recently, Kraft et al. presented a family expression association test (FEXAT) for correlation between gene expressions and trait values with a family-based (sibships) design. This statistic did not account for biological relationships of related subjects, which may inflate type I error rate and/or decrease power of statistical tests. In this article, we propose two new test statistics based on a variance-components approach for analyses of microarray data obtained from general pedigrees. Our methods accommodate covariance between relatives for unmeasured genetic effects and directly model covariates of clinical importance. The efficacy and validity of our methods are investigated by using simulated data under different sample sizes, family sizes, and family structures. The proposed LR method has correct type I error rate with moderate to large sample sizes regardless of family structure and family sizes. It has higher power with complex pedigrees and similar power to the FEXAT with sibships. The other proposed FEXAT(R) method is favorable with large family sizes, regardless of sample sizes and family structure. Our methods, robust to population stratification, are complementary to the FEXAT in expression-trait association studies.

Contribution of genotype and ethnicity to bone mineral density variation in Caucasians and Chinese: a test for five candidate genes for bone mass.

BACKGROUND: Ethnicity is shown to be one of important factors affecting bone mineral density (BMD). The present study was performed to compare the association of six markers for five candidate genes with BMD variation in two populations of different ethnicity, Caucasian and Chinese, and the contribution of genotype and ethnicity to this variation in the populations. METHODS: The studied restriction fragment length polymorphisms were BsaH I of the calcium-sensing receptor gene, SacI of the alpha2HS-glycoprotein (AHSG) gene, PvuII and XbaI of the oestrogen receptor alpha gene, ApaI of the vitamin D receptor (VDR) gene and BstBI of the parathyroid hormone gene. The association of these markers with BMD was analysed by one-way and two-way ANOVA with adjustment for covariates. RESULTS: Two polymorphisms, AHSG-SacI and VDR-ApaI, showed no association with BMD, while the others were associated with BMD variation at some skeletal sites in either males or females. The polymorphisms indicated clear distinctions between the associations depending on ethnicity, gender and skeletal site. Similar patterns were observed in their contribution to the total population BMD variation. Ethnicity appears to have a larger effect on the total population BMD variation in females than in males. It may account, on the average, for about 2% total population BMD variation at the spine of females and about 1% at the hip of males and females. CONCLUSION: The results of the present study suggest that significant interethnic differentiation at some loci may contribute to the significant interethnic difference in BMD. However, this contribution apparently is not large.

Tests of linkage and/or association of the LEPR gene polymorphisms with obesity phenotypes in Caucasian nuclear families.

Genetic variations in the leptin receptor (LEPR) gene have been conceived to affect body weight in general populations. In this study, using the tests implemented in the statistical package QTDT, we evaluated association and/or linkage of the LEPR gene with obesity phenotypes in a large sample comprising 1,873 subjects from 405 Caucasian nuclear families. Obesity phenotypes tested include body mass index (BMI), fat mass, percentage fat mass (PFM), and lean mass, with the latter three measured by dual-energy X-ray absorptiometry (DXA). Three single nucleotide polymorphisms (SNPs), namely Lys109Arg (A/G), Lys656Asn (G/C), Pro1019Pro (G/A), in the LEPR gene were analyzed. Significant linkage disequilibrium (0.394 < or = |D'| < or = 0.688, P < 0.001) was observed between pairs of the three SNPs. No significant population stratification was found for any SNP/phenotype. In single-locus analyses, evidence of association was observed for Lys656Asn with lean mass (P = 0.002) and fat mass (P = 0.015). The contribution of this polymorphism to the phenotypic variation of lean mass and fat mass was 2.63% and 1.15%, respectively. Subjects carrying allele G at the Lys656Asn site had, on average, 3.16% higher lean mass and 2.71% higher fat mass than those without it. In the analyses for haplotypes defined by the three SNPs, significant associations were detected between haplotype GCA (P = 0.005) and lean mass. In addition, marginally significant evidence of association was observed for this haplotype with fat mass (P = 0.012). No statistically significant linkage was found, largely due to the limited power of the linkage approach to detect small genetic effects in our data sets. Our results suggest that the LEPR gene polymorphisms contribute to variation in obesity phenotypes.

Association between COL1A1 gene polymorphisms and bone size in Caucasians.

Bone size is an important determinant of bone strength and a risk factor of osteoporotic fracture. Several studies indicate that bone size has a high heritability. Thus, a better understanding of genetic factors regulating bone size might have important clinical implications. In the present study, we examined the relationship between the collagen type I alpha 1 (COL1A1) gene and bone size at the spine, hip and wrist in a sample of 1873 subjects of Caucasian origin from 405 nuclear families. Three single-nucleotide polymorphisms (SNPs) in the COL1A1 gene were analyzed. The minor allele frequencies were 15.4, 18.8, and 1.9% for SNP1, SNP2, and SNP3, respectively. Haplotypes were reconstructed based on the family information as well as marker genotypes using the program Genehunter. We did not find evidence of population stratification, within-family association, or linkage for either single SNPs or haplotypes at any skeletal site. Suggestive evidence of total association was observed for the wrist size at SNP2 (P=0.011). After adjusting age, sex, height, and weight, subjects with the T allele of SNP2 had, on average, 3.05% smaller wrist size than noncarriers. When the subjects were divided into families with only female offspring and families with male offspring only, similar total associations were found at the wrist size for SNP2 with P-values of 0.011 and 0.010, respectively. In conclusion, the COL1A1 gene may have some effects on bone size variation at the wrist, but not at the spine or hip in our Caucasian nuclear families.

Test of linkage and/or association between the estrogen receptor alpha gene with bone mineral density in Caucasian nuclear families.

Extensive studies have been performed on the association between the estrogen receptor alpha (ER-alpha) gene and bone mineral density (BMD). Despite considerable efforts, the studies using limited markers and relatively small sample size have yielded largely inconsistent results. In this study, 1873 Caucasian subjects from 405 nuclear families containing 1512 sib pairs were recruited. BMD at the lumbar spine (LS) and femoral neck (FN) was measured by dual-energy X-ray absorptiometry (DXA). Seven single-nucleotide polymorphisms (SNPs) spanning from exon 1 to 8 in the ER-alpha gene were genotyped. The program QTDT (quantitative transmission disequilibrium test) was applied to test linkage and/or association of the ER-alpha gene and BMD variation using individual SNP markers and reconstructed haplotypes. Linkage disequilibrium (LD) was generally detected for SNPs in the ER-a gene (P < 0.05). Associations were observed between SNP rs932477 and FN BMD (P = 0.028), and between the most predominant three-marker haplotype (GCG) containing SNP rs932477 and FN BMD (P = 0.010). Within-family association (present only with both linkage and association) between SNP rs2228480 (G2014A) and FN BMD (P = 0.015) was observed. The most predominant seven-SNP haplotype (TCGCGGG) was associated with higher LS BMD (P = 0.015). However, after correction for multiple testing, these associations did not reach statistical significance. Denser markers may be necessary to better define the relationship between the ER-alpha gene and BMD variation in our sample.

Current limitations of SNP data from the public domain for studies of complex disorders: a test for ten candidate genes for obesity and osteoporosis.

BACKGROUND: Public SNP databases are frequently used to choose SNPs for candidate genes in the association and linkage studies of complex disorders. However, their utility for such studies of diseases with ethnic-dependent background has never been evaluated. RESULTS: To estimate the accuracy and completeness of SNP public databases, we analyzed the allele frequencies of 41 SNPs in 10 candidate genes for obesity and/or osteoporosis in a large American-Caucasian sample (1,873 individuals from 405 nuclear families) by PCR-invader assay. We compared our results with those from the databases and other published studies. Of the 41 SNPs, 8 were monomorphic in our sample. Twelve were reported for the first time for Caucasians and the other 29 SNPs in our sample essentially confirmed the respective allele frequencies for Caucasians in the databases and previous studies. The comparison of our data with other ethnic groups showed significant differentiation between the three major world ethnic groups at some SNPs (Caucasians and Africans differed at 3 of the 18 shared SNPs, and Caucasians and Asians differed at 13 of the 22 shared SNPs). This genetic differentiation may have an important implication for studying the well-known ethnic differences in the prevalence of obesity and osteoporosis, and complex disorders in general. CONCLUSION: A comparative analysis of the SNP data of the candidate genes obtained in the present study, as well as those retrieved from the public domain, suggests that the databases may currently have serious limitations for studying complex disorders with an ethnic-dependent background due to the incomplete and uneven representation of the candidate SNPs in the databases for the major ethnic groups. This conclusion attests to the imperative necessity of large-scale and accurate characterization of these SNPs in different ethnic groups.