Biomedical subjects

Yan-Fang Guo

Publications and source records attributed to Yan-Fang Guo.

13 recordsLinked to original sources

PubMed2006

Evaluating the correlation and prediction of trunk fat mass with five anthropometric indices in Chinese females aged 20-40 years.

BACKGROUND AND AIMS: Obesity is a worldwide problem, and excess trunk fat mass (FM(trunk)) has been associated with an increased risk of diseases. The early measurement of FM(trunk) has potential importance to evaluate trunk obesity. We sought to evaluate the correlation and predication of FM(trunk) with five anthropometric indices in Chinese females. METHODS AND RESULTS: A sample of 850 China females aged 20-40 years were recruited and divided into four age groups with a 5-year range in each group. Five anthropometric indices were measured or calculated. FM(trunk) in kg was measured using a dual-energy X-ray absorptiometry scanner. Principal component analysis (PCA) and multiple regression analysis were performed to develop prediction equations. There was an increasing trend of FM(trunk) and five anthropometric indices in successively older age groups. Four formed principal components (PCs) interpreted over 99% of the total variation of five relative anthropometric indices in all age groups. Regression analyses showed that four PCs combined explained a greater variance (R(2)=45.2-81.6%) in FM(trunk) than did each of the five indices alone (R(2)=2.4-72.2%). CONCLUSIONS: Our results suggested that there is an increasing trend of FM(trunk) and five anthropometric indices with aging; that age obviously influences the relationship of FM(trunk) and the anthropometric indices studied; and that the accuracy of predicting the FM(trunk) using five anthropometric indices combined is greater than using the five indices alone.

Absorptiometry, Photon↗

PubMed2006

Is a gene important for bone resorption a candidate for obesity? An association and linkage study on the RANK (receptor activator of nuclear factor-kappaB) gene in a large Caucasian sample.

In light of findings that osteoporosis and obesity may share some common genetic determination and previous reports that RANK (receptor activator of nuclear factor-kappaB) is expressed in skeletal muscles which are important for energy metabolism, we hypothesize that RANK, a gene essential for osteoclastogenesis, is also important for obesity. In order to test the hypothesis with solid data we first performed a linkage analysis around the RANK gene in 4,102 Caucasian subjects from 434 pedigrees, then we genotyped 19 SNPs in or around the RANK gene. A family-based association test (FBAT) was performed with both a quantitative measure of obesity [fat mass, lean mass, body mass index (BMI), and percentage fat mass (PFM)] and a dichotomously defined obesity phenotype-OB (OB if BMI > or = 30 kg/m(2)). In the linkage analysis, an empirical P = 0.004 was achieved at the location of the RANK gene for BMI. Family-based association analysis revealed significant associations of eight SNPs with at least one obesity-related phenotype (P < 0.05). Evidence of association was obtained at SNP10 (P = 0.002) and SNP16 (P = 0.001) with OB; SNP1 with fat mass (P = 0.003); SNP1 (P = 0.003) and SNP7 (P = 0.003) with lean mass; SNP1 (P = 0.002) and SNP7 (P = 0.002) with BMI; SNP1 (P = 0.003), SNP4 (P = 0.007), and SNP7 (P = 0.002) with PFM. In order to deal with the complex multiple testing issues, we performed FBAT multi-marker test (FBAT-MM) to evaluate the association between all the 18 SNPs and each obesity phenotype. The P value is 0.126 for OB, 0.033 for fat mass, 0.021 for lean mass, 0.016 for BMI, and 0.006 for PFM. The haplotype data analyses provide further association evidence. In conclusion, for the first time, our results suggest that RANK is a novel candidate for determination of obesity.

Adult↗

PubMed2006

Receiver-operating characteristic analyses of body mass index, waist circumference and waist-to-hip ratio for obesity: Screening in young adults in central south of China.

BACKGROUND & AIMS: Recent data suggest that current obesity diagnostic criterion based on body mass index (BMI) above 30 in Caucasians may not be appropriate for Asian populations. Our aim was to identify the usefulness of BMI, waist circumference (WC) and waist-to-hip ratio (WHR) in screening for obesity in an Asian population. METHODS: A cross-sectional sample of 1109 males and 879 females aged 20-45-yr were recruited. Height, weight, WC, hip circumference and percentage body fat (PBF) were measured in all subjects. Then receiver-operating characteristic analyses were used to evaluate the performances of the three anthropometric indices. RESULTS: BMI, WC and WHR showed strong positive correlation with PBF (r=0.47-0.75) in both males and females within both age groups. True-positive rates ranged from 82.4% to 94.1% and 68.8% to 86.3% in males and females, respectively. True-negative rates ranged from 64.1% to 84.7% and from 56.9% to 79.0%, respectively. The areas under the curves (AUCs) for WC and BMI were high (0.76-0.92) in both sexes and divided age groups (20-30-yr and 31-45-yr), and those for WHR were a little lower (0.74-0.88). CONCLUSIONS: BMI and WC are two important predictors for obesity in Chinese, and WHR is an alternative.

Adipose Tissue↗

PubMed2006

Epistasis between loci on chromosomes 2 and 6 influences human height.

CONTEXT: Human height is a typical and important complex trait, which is determined by both actions and interactions of multiple genes. Although an increasing number of genes or genomic regions have been discovered for their independent effects on height variation, no study has been performed to identify genes or loci that interact to control the trait. OBJECTIVE: This study aimed to search for potential genomic regions that harbor interactive genes underlying human height. METHODS: Here with a sample containing 3726 Caucasians, the largest one ever obtained from a single population of the same ethnicity among genetic linkage studies of human complex traits, we performed variance component linkage analyses of height based on a two-locus epistatic model. We examined pairwise genetic interaction among three regions, 9q22, 6p21, and 2q21, which achieved significant or suggestive linkage signals for height in our recent whole genome scan. RESULTS: Significant genetic interaction between 6p21 and 2q21 was detected, with 2q21 achieving a maximum LOD score of 3.21 (P = 0.0035) under the epistatic model, compared with a maximum LOD score of 1.63 under a two-locus additive model. Interestingly, 6p21 contains a cluster of candidate genes for skeletal growth, suggesting a mechanism whereby 2q21 regulates height through 6p21. CONCLUSION: By providing the first evidence for genetic interaction underlying human height variation, this study further delineated the genetic architecture of human height and contributed to the genetic dissection of human complex traits in general.

Adult↗

PubMed2006

Assessment of genetic linkage and parent-of-origin effects on obesity.

CONTEXT: Obesity is a growing health care problem worldwide and is a major underlying risk factor for common diseases such as diabetes. Parent-of-origin effect has been reported to be involved in the development of obesity. But the genes with imprinting effects related to obesity are largely unknown. OBJECTIVE: The objective of the study was to identify obesity-related genetic loci, both with and without imprinting effects. DESIGN AND SUBJECTS: We conducted genome-wide linkage analyses for obesity with and without consideration of imprinting effects in a large sample including more than 4000 individuals. In addition to body mass index (BMI), we also used a more stringent and accurate obesity definition, which simultaneously considers BMI and percentage of fat mass (PFM) in a gender-specific manner. Simulations were performed to identify the genome-wide significant and suggestive significant thresholds. RESULTS: In nonimprinted linkage analyses, we detected suggestive linkage at 2q31 (LOD = 2.23) and 16q22 (LOD = 1.87) for BMI and 2q37 (LOD = 2.23) for BMI and PFM. Interestingly, 2q37 also achieved a significant maternal linkage with BMI and PFM (LOD=3.34) in imprinted linkage analyses. Imprinted linkage analyses revealed suggestive linkage evidence for BMI at three additional genomic regions, including 3p14 (LOD = 2.20, paternal), 3q24 (LOD = 1.97, maternal), and 19q13 (LOD = 1.81, maternal). CONCLUSION: We reported linkage and imprinting effects for obesity on several chromosome regions and suggested the potential importance of parent-of-origin effects and phenotype definition of obesity in delineating the genetic basis of obesity.

Adipose Tissue↗

PubMed2006

Polymorphisms of estrogen-biosynthesis genes CYP17 and CYP19 may influence age at menarche: a genetic association study in Caucasian females.

Variation in age at menarche (AAM) is known to be substantially influenced by genetic factors, but the true causal genes remain largely unidentified. Because the increased amplitude of estrogen exposure of tissues initiates the onset of menarche, the genes involved in estrogen biosynthesis are natural candidate genes underlying AAM. Our study aimed to identify whether the CYP17 and CYP19, the two key genes involved in the biosynthesis of estrogen, are associated with AAM variation in 1048 females from 354 Caucasian nuclear families. We genotyped 38 SNPs and established the linkage disequilibrium blocks and haplotype structures that covered the full transcript length of those two genes. Family-based and population-based statistical analyses were used to test for associations with all of the single SNPs and haplotypes. Both methods consistently detected significant associations for five SNPs of CYP19 with AAM. Haplotype analyses corroborated our single-SNP results by showing that the haplotypes in block 1 were highly significant to AAM in population-based analyses. However, we could not find any association of CYP17 with AAM. Our study is the first to suggest the important effect of CYP19 on AAM variation in Caucasian females. It will be valuable to replicate and confirm these findings in other independent studies, aiming at eventually finding the hidden genetic mechanisms underlying the variation in AAM.

Adolescent↗

PubMed2006

Genomewide linkage scan for quantitative trait loci underlying variation in age at menarche.

CONTEXT: Age at menarche (AAM) is an important anthropological variable that has major implications for a woman's health later in life. Genetic influence has been shown to contribute greatly to AAM, but the specific genetic determinants are largely unknown. OBJECTIVE: The objective of this study was to identify the quantitative trait loci (QTL) underlying the variations in AAM. METHODS: We performed a large-scale, genomewide, linkage scan in 2461 Caucasian women from 402 pedigrees. All subjects were genotyped with 410 microsatellite markers spaced approximately 8.9 cM apart across the human genome. Using the variance component method, we conducted multipoint linkage analyses and two-locus tests for epistatic interaction. RESULTS: The strongest linkage signal was obtained at the genomic region of 22q13 (LOD, 3.70); the other two suggestive linkages were on 22q11 (LOD, 2.68) and 11q23 (LOD, 1.98), respectively. We also detected significant epistatic interaction between genomic regions 22q13 and 3q13. CONCLUSIONS: The identification of QTL and epistatic interaction in a large female sample laid a foundation for independent replication and fine-mapping studies as well as positional and functional candidate gene studies aimed at finding the causal genetic variants and hidden mechanisms concerning the variations in AAM.

Age Factors↗

PubMed2006

Correlation and prediction of trunk fat mass with four anthropometric indices in Chinese males.

To increase our understanding of the relationships of trunk fat mass (FMtrunk) and four anthropometric indices in Chinese males, 1090 males aged 20-40 years were randomly recruited from the city of Changsha, China. Waist circumference (WC) and hip circumference (HC) were measured using standardized equipment, and three other anthropometric indices of BMI, waist:hip ratio (WHR) and conicity index (CoI) were calculated using weight, height, HC and WC. FMtrunk (in kg) was measured using a Hologic QDR 4500 W dual-energy X-ray absorptiometry scanner. There was an increasing trend of FMtrunk, %FMtrunk (percentage of FMtrunk) and BMI, WC, WHR, CoI in successively older age groups (e.g. the mean FMtrunk values were 4.63 (SD 2.58), 5.39 (SD 2.74), 5.93 (SD 2.82), 6.57 (SD 2.94) in four 5-year age groups, respectively). FMtrunk and %FMtrunk were significantly correlated with four anthropometric indices with the Pearson's correlation coefficients ranging from 0.25 to 0.86. Principal component analysis was performed to form three principal components that interpreted over 99.5% of the total variation of four related anthropometric indices in all age groups, with over 65% of the total variation accounted by principal component 1. Multiple regression analyses showed that three principal components explained a greater variance (R(2) 70.0-80.1%) in FMtrunk than did BMI or WC alone (R(2) 57.8-74.1%). The present results suggest that there is an increasing trend of FMtrunk and four anthropometric indices in successively older age groups; that age has important effects on the relationships of FMtrunk and studied anthropometric indices; and that the accuracy of predicting FMtrunk using four anthropometric indices is higher than using BMI or WC alone.

Adipose Tissue↗

PubMed2006

Genomic regions identified for BMD in a large sample including epistatic interactions and gender-specific effects.

UNLABELLED: A genome-wide linkage scan was conducted using a large white sample to identify QTLs for BMD. We found QTLs in the total sample and the gender-specific subgroups, as well as significant epistatic interactions underlying BMD variations. INTRODUCTION: Low BMD is an important risk factor for osteoporosis and under strong genetic control. MATERIALS AND METHODS: To identify quantitative trait loci (QTLs) for regulation of BMD, we performed a large-scale whole genome linkage scan (WGS) involving 4126 individuals from 451 families. In addition to the conventional linkage analyses in the total combined sample of males and females, we conducted epistatic interaction analyses and gender-specific linkage analyses. RESULTS: Significant linkage was detected on 5q23 for wrist BMD (LOD = 3.39) and 15q13 for female spine BMD (LOD = 4.49). For spine BMD, we revealed significant epistatic interactions between 3p25 and 2q32 (p = 0.0022) and between 3p25 and 11q23 (p = 0.0007). We replicated several genomic regions that showed linkage with BMD in previous studies by others and ours, such as 3p21, 1p36, and Xq27. CONCLUSIONS: This study highlights the importance of large sample size, incorporation of epistatic interaction, and consideration of gender-specific effects in identifying QTLs for BMD variation. The results of this study provide a foundation for the future fine mapping and gene identification in our population.

Bone Density↗

PubMed2006

Robust and comprehensive analysis of 20 osteoporosis candidate genes by very high-density single-nucleotide polymorphism screen among 405 white nuclear families identified significant association and gene-gene interaction.

UNLABELLED: Many "novel" osteoporosis candidate genes have been proposed in recent years. To advance our knowledge of their roles in osteoporosis, we screened 20 such genes using a set of high-density SNPs in a large family-based study. Our efforts led to the prioritization of those osteoporosis genes and the detection of gene-gene interactions. INTRODUCTION: We performed large-scale family-based association analyses of 20 novel osteoporosis candidate genes using 277 single nucleotide polymorphisms (SNPs) for the quantitative trait BMD variation and the qualitative trait osteoporosis (OP) at three clinically important skeletal sites: spine, hip, and ultradistal radius (UD). MATERIALS AND METHODS: One thousand eight hundred seventy-three subjects from 405 white nuclear families were genotyped and analyzed with an average density of one SNP per 4 kb across the 20 genes. We conducted association analyses by SNP- and haplotype-based family-based association test (FBAT) and performed gene-gene interaction analyses using multianalytic approaches such as multifactor-dimensionality reduction (MDR) and conditional logistic regression. RESULTS AND CONCLUSIONS: We detected four genes (DBP, LRP5, CYP17, and RANK) that showed highly suggestive associations (10,000-permutation derived empirical global p < or = 0.01) with spine BMD/OP; four genes (CYP19, RANK, RANKL, and CYP17) highly suggestive for hip BMD/OP; and four genes (CYP19, BMP2, RANK, and TNFR2) highly suggestive for UD BMD/OP. The associations between BMP2 with UD BMD and those between RANK with OP at the spine, hip, and UD also met the experiment-wide stringent criterion (empirical global p < or = 0.0007). Sex-stratified analyses further showed that some of the significant associations in the total sample were driven by either male or female subjects. In addition, we identified and validated a two-locus gene-gene interaction model involving GCR and ESR2, for which prior biological evidence exists. Our results suggested the prioritization of osteoporosis candidate genes from among the many proposed in recent years and revealed the significant gene-gene interaction effects influencing osteoporosis risk.

Adult↗

PubMed2005

Genome-wide scan identified QTLs underlying femoral neck cross-sectional geometry that are novel studied risk factors of osteoporosis.

UNLABELLED: A genome-wide screen was conducted using a large white sample to identify QTLs for FNCS geometry. We found significant linkage of FNCS parameters to 20q12 and Xq25, plus significant epistatic interactions and sex-specific QTLs influencing FNCS geometry variation. INTRODUCTION: Bone geometry, a highly heritable trait, is a critical component of bone strength that significantly determines osteoporotic fracture risk. Specifically, femoral neck cross-sectional (FNCS) geometry is significantly associated with hip fracture risk as well as genetic factors. However, genetic research in this respect is still in its infancy. MATERIALS AND METHODS: To identify the underlying genomic regions influencing FNCS variables, we performed a remarkably large-scale whole genome linkage scan involving 3998 individuals from 434 pedigrees for four FNCS geometry parameters, namely buckling ratio (BR), cross-sectional area (CSA), cortical thickness (CT), and section modulus (Z). The major statistical approach adopted is the variance component method implemented in SOLAR. RESULTS: Significant linkage evidence (threshold LOD = 3.72 after correction for tests of multiple phenotypes) was found in the regions of 20q12 and Xq25 for CT (LOD = 4.28 and 3.90, respectively). We also identified eight suggestive linkage signals (threshold LOD = 2.31 after correction for multiple tests) for the respective geometry traits. The above findings were supported by principal component linkage analysis. Of them, 20q12 was of particular interest because it was linked to multiple FNCS geometry traits and significantly interacted with five other genomic loci to influence CSA variation. The effects of 20q12 on FNCS geometry were present in both male and female subgroups. Subgroup analysis also revealed the presence of sex-specific quantitative trait loci (QTLs) for FNCS traits in the regions such as 2p14, 3q26, 7q21 and 15q21. CONCLUSIONS: Our findings laid a foundation for further replication and fine-mapping studies as well as for positional and functional candidate gene studies, aiming at eventually finding the causal genetic variants and hidden mechanisms concerning FNCS geometry variation and the associated hip fractures.

Adult↗

PubMed2005

Association tests of interleukin-6 (IL-6) and type II tumor necrosis factor receptor (TNFR2) genes with bone mineral density in Caucasians using a re-sampling approach.

Interleukin 6 (IL-6) and tumor necrosis factor (TNF) are important cytokines for bone turnover. In this study, a promoter C-174G single-nucleotide polymorphism (SNP) within the IL-6 gene affecting the transcription rate of IL-6 and an exon 6 T676G SNP of the TNF receptor 2 (TNFR2) gene causing an M196R amino-acid change were examined for their relationship with bone mineral density (BMD). Four hundred and five multi-offspring Caucasian families, including 389 male children and 744 female children, were used. One thousand re-samplings were conducted and in each data set, one child was randomly chosen from each family. For each data set, one-way analysis of variance (ANOVA) test was independently implemented using age, age2, sex, height and weight as covariates. There were 523, 288, 204 and 369 significant results out of 1,000-replicate re-samplings of the data of the IL-6 SNP (P<0.05) for one-third, mid-distal, ultradistal radius BMD, and the first principal component (PC1) extracted from the three radial BMDs, respectively, which means that the confidences for associations of the C-174G SNP in the IL-6 gene with one-third, mid-distal, ultradistal radius (totally called distal forearm) BMDs, and PC1, were 52.3, 28.8, 20.4 and 36.9%, respectively. For this SNP with BMD at other skeletal sites and the TNFR2 T676G SNP with BMD at any site, significant results were far less than 200 times out of 1,000 re-sampling replicates. The exceedingly consistent permutation results further improved the confidence of the associations. It may imply that the IL-6 C-174G SNP is associated with distal forearm BMD, but there is no evidence that the TNFR2 T676G SNP is related with BMD in US Caucasians. This is the first attempt to conduct association test utilizing a re-sampling approach. Our results may be more informative than other association analyses that were only based on one sampling result. The results also suggest that different samplings could produce significantly diverse results even for the same population and the results from one sampling are unlikely to be conclusive. Our results have significant implications for association studies and interpretation of non-reproducible association findings.

Body Weights and Measures↗

PubMed2004

SNPP: automating large-scale SNP genotype data management.

UNLABELLED: To manage high-throughput single nucleotide polymorphism (SNP) genotyping data efficiently, we developed a dynamic general database management system-SNPP (SNP Processor). It provides several functions, including data importing with comparison, Mendelian inheritance check within pedigrees, data compiling and exporting. Furthermore, SNPP may generate files for repeat genotyping and transform them into files that can be executed by a liquid handling system. AVAILABILITY: http://orclinux.creighton.edu/snpp/ CONTACT: lanjuanzhao@creighton.edu

Algorithms↗