IntroductionVegetarian diets have been shown to improve glucose metabolism and reduce risk for diabetes in Westerners but whether Chinese vegetarian diets have the same benefits is unknown.MethodsWe evaluated the association between diet and diabetes/impaired fasting glucose (IFG) among 4384 Taiwanese Buddhist volunteers and identified diabetes/IFG cases from a comprehensive review of medical history and fasting plasma glucose.ResultsVegetarians had higher intakes of carbohydrates, fiber, calcium, magnesium, total and non-heme iron, folate, vitamin A, and lower intakes of saturated fat, cholesterol, and vitamin B12. Besides avoiding meat and fish, vegetarians had higher intakes of soy products, vegetables, whole grains, but similar intakes of dairy and fruits, compared with omnivores. The crude prevalence of diabetes in vegetarians versus omnivores is 0.6% versus 2.3% in pre-menopausal women, 2.8% versus 10% in menopausal women, and 4.3% versus 8.1% in men. Polytomous logistic regression adjusting for age, body mass index, family history of diabetes, education, leisure time physical activity, smoking and alcohol, showed that this vegetarian diet was negatively associated with diabetes and IFG in men (OR for diabetes: 0.49, 95% CI: 0.28–0.89; OR for IFG: 0.66, 95% CI: 0.46–0.95); in pre-menopausal women (OR for diabetes: 0.26, 95% CI: 0.06–1.21; OR for IFG: 0.60, 95% CI: 0.35–1.04); and in menopausal women (OR for diabetes: 0.25, 95% CI: 0.15–0.42; OR for IFG: 0.73, 95% CI: 0.56–0.95).ConclusionWe found a strong protective association between Taiwanese vegetarian diet and diabetes/IFG, after controlling for various potential confounders and risk factors.

To dissect the genetic architecture of sexual dimorphism in obesity-related traits, we evaluated the sex–genotype interaction, sex-specific heritability and genome-wide linkages for seven measurements related to obesity. A total of 1,365 non-diabetic Chinese subjects from the family study of the Stanford Asia–Pacific Program of Hypertension and Insulin Resistance were used to search for quantitative trait loci (QTLs) responsible for the obesity-related traits. Pleiotropy and co-incidence effects from the QTLs were also examined using the bivariate linkage approach. We found that sex-specific differences in heritability and the genotype–sex interaction effects were substantially significant for most of these traits. Several QTLs with strong linkage evidence were identified after incorporating genotype by sex (G × S) interactions into the linkage mapping, including one QTL for hip circumference [maximum LOD score (MLS) = 4.22, empirical p = 0.000033] and two QTLs: for BMI on chromosome 12q with MLS 3.37 (empirical p = 0.0043) and 3.10 (empirical p = 0.0054). Sex-specific analyses demonstrated that these linkage signals all resulted from females rather than males. Most of these QTLs for obesity-related traits replicated the findings in other ethnic groups. Bivariate linkage analyses showed several obesity traits were influenced by a common set of QTLs. All regions with linkage signals were observed in one gender, but not in the whole sample, suggesting the genetic architecture of obesity-related traits does differ by gender. These findings are useful for further identification of the liability genes for these phenotypes through candidate genes or genome-wide association analysis.

Circadian clock genes are critical regulators of energy homeostasis and metabolism. However, whether variation in the circadian genes is associated with metabolic phenotypes in humans remains to be explored. In this study, we systemically genotyped 20 tag single nucleotide polymorphisms (SNPs) in 8 candidate genes involved in circadian clock, including CLOCK, BMAL1(ARNTL), PER1, PER2, CRY1, CRY2, CSNK1E,, and NOC(CCRN4L) in 1,510 non-diabetic Chinese subjects in Taipei and Yunlin populations in Taiwan. Their associations with metabolic phenotypes were analyzed. We found that genetic variation in the NOC gene, rs9684900 was associated with body mass index (BMI) (P = 0.0016, Bonferroni corrected P = 0.032). Another variant, rs135764 in the CSNK1E gene was associated with fasting glucose (P = 0.0023, Bonferroni corrected P = 0.046). These associations were consistent in both Taipei and Yunlin populations. Significant epistatic and joint effects between SNPs on BMI and related phenotypes were observed. Furthermore, NOC mRNA levels in human abdominal adipose tissue were significantly increased in obese subjects compared to non-obese controls.ConclusionGenetic variation in the NOC gene is associated with BMI in Chinese subjects.

We conducted linkage analysis using the genome-wide association study data on chromosome 3, and then assessed association between hypertension and rare variants of genes located in the regions showing evidence of linkage. The rare variants were collapsed if their minor allele frequencies were less than or equal to the thresholds: 0.01, 0.03, or 0.05. In the collapsing process, they were either unweighted or weighted by the nonparametric linkage log of odds scores in 2 different schemes: exponential weighting and cumulative weighting. Logistic regression models using the generalized estimating equations approach were used to assess association between the collapsed rare variants and hypertension adjusting for age and gender. Evidence of association from the weighted and unweighted collapsing schemes with minor allele frequencies ≤0.01, after accounting for multiple testing, was found for genes DOCK3 (p = 0.0090), ARMC8 (p = 1.29E-5), KCNAB1 (p = 5.8E-4), and MYRIP (p = 5.79E-6). DOCK3 and MYRIP are newly discovered. Incorporating linkage scores as weights was found to help identify rare causal variants with a large effect size.

Aims/hypothesis Hypertension, obesity, impaired glucose tolerance and dyslipidaemia are metabolic abnormalities that often cluster together more often than expected by chance alone. Since these metabolic variables are highly heritable and are at least partially genetically determined, the clustering of defects in these traits implies that pleiotropic effects, where a common set of genes influences more than one trait simultaneously, are likely.Methods We conducted bivariate linkage analyses for highly correlated traits, aiming to dissect the genetic architecture affecting these traits, in 411 Chinese families participating in the Stanford Asia-Pacific Program of Hypertension and Insulin Resistance Study. Results We confirmed the pleiotropic effects of the locus at 37 cM on chromosome 20 on the following pairs: (1) fasting insulin and insulin AUC (empirical p=0.0006); (2) fasting insulin and homeostasis model assessment of

SummaryWe report two methods for linkage disequilibrium mapping that involve incorporation of covariates through parametric modeling to utilize combined case-parent trios and unrelated case and/or control data. The proposed two combined methods were used to map the disease locus of hypertension in the angiotensin-converting enzyme (ACE) gene with incorporation of ACE activity. The efficiencies in estimating the disease locus increased by 351-and 100-fold in the hybrid study with respect to the two proposed methods when compared to the estimates from the trios study; and they changed by 1.4-and 0.4-fold, respectively, when compared to the case-control study. Efficiency of disease locus estimates was greatly improved in both simulations and hypertension studies based on the hybrid data, compared to case-parent trio studies only. These newly developed methods preserve the advantages of the previous methods, including flexible modeling and assessment of gene-gene and gene-covariate effects, while providing more power by using all the data combined. The computing program for analysis using the separate and hybrid data sets is freely available on the author's website.

The HLA region is considered to be the main genetic risk factor for rheumatoid arthritis. Previous research demonstrated that HLA-DRB1 alleles encoding the shared epitope are specific for disease that is characterized by antibodies to cyclic citrullinated peptides (anti-CCP). In the present study, we incorporated the shared epitope and either anti-CCP antibodies or rheumatoid factor into linkage disequilibrium mapping, to assess the association between the shared epitope or antibodies with the disease gene identified. Incorporating the covariates into the association mapping provides a mechanism 1) to evaluate gene-gene and gene-environment interactions and 2) to dissect the pathways underlying disease induction/progress in quantitative antibodies.

Rheumatoid arthritis is a complex disease in which environmental factors interact with genetic factors that influence susceptibility. Incorporating information about related quantitative traits or environmental factors into linkage mapping could therefore greatly improve the efficiency and precision of identifying the disease locus. Using a multipoint linkage approach that allows the incorporation of quantitative variables into multipoint linkage mapping based on affected sib pairs, we incorporated data on anti-cyclic citrullinated peptide antibodies, immunoglobulin M rheumatoid factor and age at onset into genome-wide linkage scans. The strongest evidence of linkage was observed on chromosome 6p with a p-value of 3.8 × 10-15 for the genetic effect. The trait locus is estimated at approximately 45.51–45.82 cM, with standard errors of the estimates range from 0.82 to 1.26 cM, depending on whether and which quantitative variable is incorporated. The standard error of the estimate of trait locus decreased about 28% to 35% after incorporating the additional information from the quantitative variables. This mapping technique helps to narrow down the regions of interest when searching for a susceptibility locus and to elucidate underlying disease mechanisms.