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1.  Multipoint association mapping for longitudinal family data: an application to hypertension phenotypes 
BMC Proceedings  2016;10(Suppl 7):315-320.
It is essential to develop adequate statistical methods to fully utilize information from longitudinal family studies. We extend our previous multipoint linkage disequilibrium approach—simultaneously accounting for correlations between markers and repeat measurements within subjects, and the correlations between subjects in families—to detect loci relevant to disease through gene-based analysis. Estimates of disease loci and their genetic effects along with their 95 % confidence intervals (or significance levels) are reported. Four different phenotypes—ever having hypertension at 4 visits, incidence of hypertension, hypertension status at baseline only, and hypertension status at 4 visits—are studied using the proposed approach. The efficiency of estimates of disease locus positions (inverse of standard error) improves when using the phenotypes from 4 visits rather than using baseline only.
PMCID: PMC5133529  PMID: 27980655
2.  Incorporating Covariates into Multipoint Association Mapping in the Case-Parent Design 
Human Heredity  2010;69(4):229-241.
To improve the efficiency of disease locus localization in association mapping using case-parent designs and to assess or account for the main covariate effects and gene-covariate interaction effects, while localizing the disease locus.
The present study extends a multipoint fine-mapping approach to incorporate covariates into the association mapping of case-parent designs through parametric and non-parametric modeling. This approach is based on the expected preferential-allele-transmission statistics for transmission from either parent to an affected child.
Simulation studies indicate that the efficiency in estimating the disease locus increases considerably when incorporating a covariate associated with the disease. This is especially true when the genetic effect of the disease locus is small. The proposed approach was applied to a young-onset hypertension data sample. The relative efficiency of estimating the locus of young-onset hypertension increases 110-fold after incorporating triglyceride into the association mapping while localizing the disease variant in the lipoprotein lipase gene in the non-parametric model. By incorporating the information of SNP variants into the fine-mapping, the proposed method further assesses the gene-gene interactions between the SNP and the disease locus.
With the incorporation of covariates, the proposed method cannot only improve efficiency in estimating disease loci, but can also elucidate the etiology of a complex disease.
PMCID: PMC2889259  PMID: 20332647
Case-parent designs; Gene-gene interactions; Gene-environment interactions; Gene-covariate interactions; Relative efficiency; Parametric; Non-parametric
3.  Genetics of Coronary Artery Disease in Taiwan: A Cardiometabochip Study by the Taichi Consortium 
PLoS ONE  2016;11(3):e0138014.
By means of a combination of genome-wide and follow-up studies, recent large-scale association studies of populations of European descent have now identified over 46 loci associated with coronary artery disease (CAD). As part of the TAICHI Consortium, we have collected and genotyped 8556 subjects from Taiwan, comprising 5423 controls and 3133 cases with coronary artery disease, for 9087 CAD SNPs using the CardioMetaboChip. We applied penalized logistic regression to ascertain the top SNPs that contribute together to CAD susceptibility in Taiwan. We observed that the 9p21 locus contributes to CAD at the level of genome-wide significance (rs1537372, with the presence of C, the major allele, the effect estimate is -0.216, standard error 0.033, p value 5.8x10-10). In contrast to a previous report, we propose that the 9p21 locus is a single genetic contribution to CAD in Taiwan because: 1) the penalized logistic regression and the follow-up conditional analysis suggested that rs1537372 accounts for all of the CAD association in 9p21, and 2) the high linkage disequilibrium observed for all associated SNPs in 9p21. We also observed evidence for the following loci at a false discovery rate >5%: SH2B3, ADAMTS7, PHACTR1, GGCX, HTRA1, COL4A1, and LARP6-LRRC49. We also took advantage of the fact that penalized methods are an efficient approach to search for gene-by-gene interactions, and observed that two-way interactions between the PHACTR1 and ADAMTS7 loci and between the SH2B3 and COL4A1 loci contribute to CAD risk. Both the similarities and differences between the significance of these loci when compared with significance of loci in studies of populations of European descent underscore the fact that further genetic association of studies in additional populations will provide clues to identify the genetic architecture of CAD across all populations worldwide.
PMCID: PMC4794124  PMID: 26982883
4.  Longitudinal analytical approaches to genetic data 
BMC Genetics  2016;17(Suppl 2):4.
Longitudinal phenotypic data provides a rich potential resource for genetic studies which may allow for greater understanding of variants and their covariates over time. Herein, we review 3 longitudinal analytical approaches from the Genetic Analysis Workshop 19 (GAW19). These contributions investigated both genome-wide association (GWA) and whole genome sequence (WGS) data from odd numbered chromosomes on up to 4 time points for blood pressure–related phenotypes. The statistical models used included generalized estimating equations (GEEs), latent class growth modeling (LCGM), linear mixed-effect (LME), and variance components (VC). The goal of these analyses was to test statistical approaches that use repeat measurements to increase genetic signal for variant identification.
Two analytical methods were applied to the GAW19: GWA using real phenotypic data, and one approach to WGS using 200 simulated replicates. The first GWA approach applied a GEE-based model to identify gene-based associations with 4 derived hypertension phenotypes. This GEE model identified 1 significant locus, GRM7, which passed multiple test corrections for 2 hypertension-derived traits. The second GWA approach employed the LME to estimate genetic associations with systolic blood pressure (SBP) change trajectories identified using LCGM. This LCGM method identified 5 SBP trajectories and association analyses identified a genome-wide significant locus, near ATOX1 (p = 1.0E−8). Finally, a third VC-based model using WGS and simulated SBP phenotypes that constrained the β coefficient for a genetic variant across each time point was calculated and compared to an unconstrained approach. This constrained VC approach demonstrated increased power for WGS variants of moderate effect, but when larger genetic effects were present, averaging across time points was as effective.
In this paper, we summarize 3 GAW19 contributions applying novel statistical methods and testing previously proposed techniques under alternative conditions for longitudinal genetic association. We conclude that these approaches when appropriately applied have the potential to: (a) increase statistical power; (b) decrease trait heterogeneity and standard error; (c) decrease computational burden in WGS; and (d) have the potential to identify genetic variants influencing subphenotypes important for understanding disease progression.
PMCID: PMC4895696  PMID: 26866891
5.  Genetic polymorphisms of PCSK2 are associated with glucose homeostasis and progression to type 2 diabetes in a Chinese population 
Scientific Reports  2015;5:14380.
Proprotein convertase subtilisin/kexin type 2 (PCSK2) is a prohormone processing enzyme involved in insulin and glucagon biosynthesis. We previously found the genetic polymorphism of PCSK2 on chromosome 20 was responsible for the linkage peak of several glucose homeostasis parameters. The aim of this study is to investigate the association between genetic variants of PCSK2 and glucose homeostasis parameters and incident diabetes. Total 1142 Chinese participants were recruited from the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance (SAPPHIRe) family study, and 759 participants were followed up for 5 years. Ten SNPs of the PCSK2 gene were genotyped. Variants of rs6044695 and rs2284912 were associated with fasting plasma glucose, and variants of rs2269023 were associated with fasting plasma glucose and 1-hour plasma glucose during OGTT. Haplotypes of rs4814605/rs1078199 were associated with fasting plasma insulin levels and HOMA-IR. Haplotypes of rs890609/rs2269023 were also associated with fasting plasma glucose, fasting insulin and HOMA-IR. In the longitudinal study, we found individuals carrying TA/AA genotypes of rs6044695 or TC/CC genotypes of rs2284912 had lower incidence of diabetes during the 5-year follow-up. Our results indicated that PCSK2 gene polymorphisms are associated with pleiotropic effects on various traits of glucose homeostasis and incident diabetes.
PMCID: PMC4660384  PMID: 26607656
6.  A meta-analysis of genome-wide association studies for adiponectin levels in East Asians identifies a novel locus near WDR11-FGFR2 
Human Molecular Genetics  2013;23(4):1108-1119.
Blood levels of adiponectin, an adipocyte-secreted protein correlated with metabolic and cardiovascular risks, are highly heritable. Genome-wide association (GWA) studies for adiponectin levels have identified 14 loci harboring variants associated with blood levels of adiponectin. To identify novel adiponectin-associated loci, particularly those of importance in East Asians, we conducted a meta-analysis of GWA studies for adiponectin in 7827 individuals, followed by two stages of replications in 4298 and 5954 additional individuals. We identified a novel adiponectin-associated locus on chromosome 10 near WDR11-FGFR2 (P = 3.0 × 10−14) and provided suggestive evidence for a locus on chromosome 12 near OR8S1-LALBA (P = 1.2 × 10−7). Of the adiponectin-associated loci previously described, we confirmed the association at CDH13 (P = 6.8 × 10−165), ADIPOQ (P = 1.8 × 10−22), PEPD (P = 3.6 × 10−12), CMIP (P = 2.1 × 10−10), ZNF664 (P = 2.3 × 10−7) and GPR109A (P = 7.4 × 10−6). Conditional analysis at ADIPOQ revealed a second signal with suggestive evidence of association only after conditioning on the lead SNP (Pinitial = 0.020; Pconditional = 7.0 × 10−7). We further confirmed the independence of two pairs of closely located loci (<2 Mb) on chromosome 16 at CMIP and CDH13, and on chromosome 12 at GPR109A and ZNF664. In addition, the newly identified signal near WDR11-FGFR2 exhibited evidence of association with triglycerides (P = 3.3 × 10−4), high density lipoprotein cholesterol (HDL-C, P = 4.9 × 10−4) and body mass index (BMI)-adjusted waist–hip ratio (P = 9.8 × 10−3). These findings improve our knowledge of the genetic basis of adiponectin variation, demonstrate the shared allelic architecture for adiponectin with lipids and central obesity and motivate further studies of underlying mechanisms.
PMCID: PMC3900106  PMID: 24105470
7.  Identification of rare variants for hypertension with incorporation of linkage information 
BMC Proceedings  2014;8(Suppl 1):S109.
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.
PMCID: PMC4144469  PMID: 25519312
8.  Taiwanese Vegetarians and Omnivores: Dietary Composition, Prevalence of Diabetes and IFG 
PLoS ONE  2014;9(2):e88547.
Vegetarian 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.
We 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.
Vegetarians 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).
We found a strong protective association between Taiwanese vegetarian diet and diabetes/IFG, after controlling for various potential confounders and risk factors.
PMCID: PMC3921224  PMID: 24523914
9.  Association between Dietary Fiber Intake and Physical Performance in Older Adults: A Nationwide Study in Taiwan 
PLoS ONE  2013;8(11):e80209.
Physical performance is a major determinant of health in older adults, and is related to lifestyle factors. Dietary fiber has multiple health benefits. It remains unclear whether fiber intake is independently linked to superior physical performance. We aimed to assess the association between dietary fiber and physical performance in older adults.
This was a cross-sectional study conducted with community-dwelling adults aged 55 years and older (n=2680) from the ongoing Healthy Aging Longitudinal Study (HALST) in Taiwan 2008-2010. Daily dietary fiber intake was assessed using a validated food frequency questionnaire. Physical performance was determined objectively by measuring gait speed, 6-minute walk distance, timed “up and go” (TUG), summary performance score, hand grip strength.
Adjusting for all potential confounders, participants with higher fiber intake had significantly faster gait speed, longer 6-minute walk distance, faster TUG, higher summary performance score, and higher hand grip strength (all P <.05). Comparing with the highest quartile of fiber intake, the lowest quartile of fiber intake was significantly associated with the lowest sex-specific quartile of gait speed (adjusted OR, 2.18 in men [95% CI, 1.33-3.55] and 3.65 in women [95% CI, 2.20-6.05]), 6-minute walk distance (OR, 2.40 in men [95% CI, 1.38-4.17] and 4.32 in women [95% CI, 2.37-7.89]), TUG (OR, 2.42 in men [95% CI, 1.43-4.12] and 3.27 in women [95% CI, 1.94-5.52]), summary performance score (OR, 2.12 in men [95% CI, 1.19-3.78] and 5.47 in women [95% CI, 3.20-9.35]), and hand grip strength (OR, 2.64 in men [95% CI, 1.61-4.32] and 4.43 in women [95% CI, 2.62-7.50]).
Dietary fiber intake was independently associated with better physical performance.
PMCID: PMC3823869  PMID: 24244650
10.  Trans-ethnic fine mapping identifies a novel independent locus at the 3′ end of CDKAL1 and novel variants of several susceptibility loci for type 2 diabetes in a Han Chinese population 
Diabetologia  2013;56(12):2619-2628.
Candidate gene and genome-wide association studies have identified ∼60 susceptibility loci for type 2 diabetes. A majority of these loci have been discovered and tested only in European populations. The aim of this study was to assess the presence and extent of trans-ethnic effects of these loci in an East Asian population.
A total of 9,335 unrelated Chinese Han individuals, including 4,535 with type 2 diabetes and 4,800 non-diabetic ethnically matched controls, were genotyped using the Illumina 200K Metabochip. We tested 50 established loci for type 2 diabetes and related traits (fasting glucose, fasting insulin, 2 h glucose). Disease association with the additive model of inheritance was analysed with logistic regression.
We found that 14 loci significantly transferred to the Chinese population, with two loci (p = 5.7 × 10−12 for KCNQ1; p = 5.0 × 10−8 for CDKN2A/B-CDKN2BAS) reaching independent genome-wide statistical significance. Five of these 14 loci had similar lead single-nucleotide polymorphisms (SNPs) as were found in the European studies while the other nine were different. Further stepwise conditional analysis identified a total of seven secondary signals and an independent novel locus at the 3′ end of CDKAL1.
These results suggest that many loci associated with type 2 diabetes are commonly shared between European and Chinese populations. Identification of population-specific SNPs may increase our understanding of the genetic architecture underlying type 2 diabetes in different ethnic populations.
Electronic supplementary material
The online version of this article (doi:10.1007/s00125-013-3047-1) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
PMCID: PMC3825282  PMID: 24013783
Ethnic difference; Genetic association; Type 2 diabetes
11.  A Novel Support Vector Machine-Based Approach for Rare Variant Detection 
PLoS ONE  2013;8(8):e71114.
Advances in next-generation sequencing technologies have enabled the identification of multiple rare single nucleotide polymorphisms involved in diseases or traits. Several strategies for identifying rare variants that contribute to disease susceptibility have recently been proposed. An important feature of many of these statistical methods is the pooling or collapsing of multiple rare single nucleotide variants to achieve a reasonably high frequency and effect. However, if the pooled rare variants are associated with the trait in different directions, then the pooling may weaken the signal, thereby reducing its statistical power. In the present paper, we propose a backward support vector machine (BSVM)-based variant selection procedure to identify informative disease-associated rare variants. In the selection procedure, the rare variants are weighted and collapsed according to their positive or negative associations with the disease, which may be associated with common variants and rare variants with protective, deleterious, or neutral effects. This nonparametric variant selection procedure is able to account for confounding factors and can also be adopted in other regression frameworks. The results of a simulation study and a data example show that the proposed BSVM approach is more powerful than four other approaches under the considered scenarios, while maintaining valid type I errors.
PMCID: PMC3737136  PMID: 23940698
12.  Genetic Variation in the NOC Gene Is Associated with Body Mass Index in Chinese Subjects 
PLoS ONE  2013;8(7):e69622.
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.
Genetic variation in the NOC gene is associated with BMI in Chinese subjects.
PMCID: PMC3724939  PMID: 23922759
13.  Common ALDH2 genetic variants predict development of hypertension in the SAPPHIRe prospective cohort: Gene-environmental interaction with alcohol consumption 
Genetic variants near/within the ALDH2 gene encoding the mitochondrial aldehyde dehydrogenase 2 have been associated with blood pressure and hypertension in several case–control association studies in East Asian populations.
Three common tag single nucleotide polymorphisms (tagSNP) in the ALDH2 gene were genotyped in 1,134 subjects of Chinese origin from the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance (SAPPHIRe) family cohort. We examined whether the ALDH2 SNP genotypes predicted the development of hypertension in the prospective SAPPHIRe cohort.
Over an average follow-up period of 5.7 years, carriers homozygous for the rs2238152 T allele in the ALDH2 gene were more likely to progress to hypertension than were non-carriers (hazard ratio [HR], 2.88, 95% confidence interval [CI], 1.06-7.84, P = 0.03), corresponding to a population attributable risk of ~7.1%. The risk associated with the rs2238152 T allele were strongest in heavy/moderate alcohol drinkers and was reduced in non-drinkers, indicating an interaction between ALDH2 genetic variants and alcohol intake on the risk of hypertension (P for interaction = 0.04). The risk allele was associated with significantly lower ALDH2 gene expression levels in human adipose tissue.
ALDH2 genetic variants were associated with progression to hypertension in a prospective Chinese cohort. The association was modified by alcohol consumption.
PMCID: PMC3476438  PMID: 22839215
ALDH2; Hypertension; SNP; Chinese
14.  Central obesity is important but not essential component of the metabolic syndrome for predicting diabetes mellitus in a hypertensive family-based cohort. Results from the Stanford Asia-pacific program for hypertension and insulin resistance (SAPPHIRe) Taiwan follow-up study 
Metabolic abnormalities have a cumulative effect on development of diabetes, but only central obesity has been defined as the essential criterion of metabolic syndrome (MetS) by the International Diabetes Federation. We hypothesized that central obesity contributes to a higher risk of new-onset diabetes than other metabolic abnormalities in the hypertensive families.
Non-diabetic Chinese were enrolled and MetS components were assessed to establish baseline data in a hypertensive family-based cohort study. Based on medical records and glucose tolerance test (OGTT), the cumulative incidence of diabetes was analyzed in this five-year study by Cox regression models. Contribution of central obesity to development of new-onset diabetes was assessed in subjects with the same number of positive MetS components.
Among the total of 595 subjects who completed the assessment, 125 (21.0%) developed diabetes. Incidence of diabetes increased in direct proportion to the number of positive MetS components (P ≪ 0.001). Although subjects with central obesity had a higher incidence of diabetes than those without (55.7 vs. 30.0 events/1000 person-years, P ≪ 0.001), the difference became non-significant after adjusting of the number of positive MetS components (hazard ratio = 0.72, 95%CI: 0.45-1.13). Furthermore, in all participants with three positive MetS components, there was no difference in the incidence of diabetes between subjects with and without central obesity (hazard ratio = 1.04, 95%CI: 0.50-2.16).
In Chinese hypertensive families, the incidence of diabetes in subjects without central obesity was similar to that in subjects with central obesity when they also had the same number of positive MetS components. We suggest that central obesity is very important, but not the essential component of the metabolic syndrome for predicting of new-onset diabetes. (Trial registration: NCT00260910,
PMCID: PMC3476431  PMID: 22537054
Metabolic syndrome; Incidence; New-onset diabetes; Obesity
15.  SLC2A10 genetic polymorphism predicts development of peripheral arterial disease in patients with type 2 diabetes. SLC2A10 and PAD in type 2 diabetes 
BMC Medical Genetics  2010;11:126.
Recent data indicate that loss-of-function mutation in the gene encoding the facilitative glucose transporter GLUT10 (SLC2A10) causes arterial tortuosity syndrome via upregulation of the TGF-β pathway in the arterial wall, a mechanism possibly causing vascular changes in diabetes.
We genotyped 10 single nucleotide polymorphisms and one microsatellite spanning 34 kb across the SLC2A10 gene in a prospective cohort of 372 diabetic patients. Their association with the development of peripheral arterial disease (PAD) in type 2 diabetic patients was analyzed.
At baseline, several common SNPs of SLC2A10 gene were associated with PAD in type 2 diabetic patients. A common haplotype was associated with higher risk of PAD in type 2 diabetic patients (haplotype frequency: 6.3%, P = 0.03; odds ratio [OR]: 14.5; 95% confidence interval [CI]: 1.3- 160.7) at baseline. Over an average follow-up period of 5.7 years, carriers with the risk-conferring haplotype were more likely to develop PAD (P = 0.007; hazard ratio: 6.78; 95% CI: 1.66- 27.6) than were non-carriers. These associations remained significant after adjustment for other risk factors of PAD.
Our data demonstrate that genetic polymorphism of the SLC2A10 gene is an independent risk factor for PAD in type 2 diabetes.
PMCID: PMC2939510  PMID: 20735855
16.  Detecting Gene-Environment Interactions in Genome-Wide Association Data 
Genetic epidemiology  2009;33(Suppl 1):S68-S73.
Despite the importance of gene-environment (G×E) interactions in the etiology of common diseases, little work has been done to develop methods for detecting these types of interactions in genome-wide association study data. This was the focus of Genetic Analysis Workshop 16 Group 10 contributions, which introduced a variety of new methods for the detection of G×E interactions in both case-control and family-based data using both cross-sectional and longitudinal study designs. Many of these contributions detected significant G×E interactions. Although these interactions have not yet been confirmed, the results suggest the importance of testing for interactions. Issues of sample size, quantifying the environmental exposure, longitudinal data analysis, family-based analysis, selection of the most powerful analysis method, population stratification, and computational expense with respect to testing G×E interactions are discussed.
PMCID: PMC2924567  PMID: 19924704
GAW; case-control; family-based; cross-sectional; longitudinal; rheumatoid arthritis; Framingham Heart Study
17.  Incorporation of covariates in simultaneous localization of two linked loci using affected relative pairs 
BMC Genetics  2010;11:67.
Many dichotomous traits for complex diseases are often involved more than one locus and/or associated with quantitative biomarkers or environmental factors. Incorporating these quantitative variables into linkage analysis as well as localizing two linked disease loci simultaneously could therefore improve the efficiency in mapping genes. We extended the robust multipoint Identity-by-Descent (IBD) approach with incorporation of covariates developed previously to simultaneously estimate two linked loci using different types of affected relative pairs (ARPs).
We showed that the efficiency was enhanced by incorporating a quantitative covariate parametrically or non-parametrically while localizing two disease loci using ARPs. In addition to its help in identifying factors associated with the disease and in improving the efficiency in estimating disease loci, this extension also allows investigators to account for heterogeneity in risk-ratios for different ARPs. Data released from the collaborative study on the genetics of alcoholism (COGA) for Genetic Analysis Workshop 14 (GAW 14) were used to illustrate the application of this extended method.
The simulation studies and example illustrated that the efficiency in estimating disease loci was demonstratively enhanced by incorporating a quantitative covariate and by using all relative pairs while mapping two linked loci simultaneously.
PMCID: PMC3247820  PMID: 20626914
18.  Assessment of gene-covariate interactions by incorporating covariates into association mapping 
BMC Proceedings  2009;3(Suppl 7):S85.
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.
PMCID: PMC2795988  PMID: 20018081
19.  Incorporating quantitative variables into linkage analysis using affected sib pairs 
BMC Proceedings  2007;1(Suppl 1):S98.
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.
PMCID: PMC2367592  PMID: 18466602
20.  Assessing genotype × environment interaction in linkage mapping using affected sib pairs 
BMC Proceedings  2007;1(Suppl 1):S71.
Rheumatoid arthritis (RA) is a complex disease that involves both environmental and genetic factors. Elucidation of the basic etiologic factors involved in RA is essential for preventing and treating this disease. However, the etiology of RA, like that of other complex diseases, is largely unknown. In the present study, we conducted autosomal multipoint linkage scans using affected sib pairs by incorporating the smoking status into analysis. We divided the affected sib pairs into three subgroups based on smoking status (ever, current, or never). Interactions between the susceptibility genes and smoking could then be assessed through linkage mapping. Results suggested that the genetic effect of chromosome 6p21.2-3 in concordant current smoker pairs was about two-fold greater than that of the concordant non-current smoker pairs or discordant pairs. With incorporation of smoking status, additional regions with evidence of linkage were identified, including chromosomes 4q and 20q; while evidence of linkage remained in the regions of chromosomes 6p, 8p, and 9p. The interaction effects varied in different regions. Results from our analyses suggested that incorporating smoking status into linkage analyses could increase the statistical power of the multipoint linkage approach applied here and help elucidate the etiology of RA.
PMCID: PMC2367488  PMID: 18466573
21.  A comparison in association and linkage genome-wide scans for alcoholism susceptibility genes using single-nucleotide polymorphisms 
BMC Genetics  2005;6(Suppl 1):S89.
We conducted genome-wide linkage scans using both microsatellite and single-nucleotide polymorphism (SNP) markers. Regions showing the strongest evidence of linkage to alcoholism susceptibility genes were identified. Haplotype analyses using a sliding-window approach for SNPs in these regions were performed. In addition, we performed a genome-wide association scan using SNP data. SNPs in these regions with evidence of association (P ≦ 0.0001) were identified. We found that the general patterns for nonparametric linkage (NPL) scores from SNP and microsatellite genome scans are fairly consistent; however, the peaks of the NPL scores are mostly higher in the SNP-based scan than those using microsatellite markers, which might be located at different regions. Furthermore, SNPs identified from linkage screens were not so strongly associated with alcoholism (the most significant SNP had a p-value of 0.030) as those identified from association genomic screening (the most significant SNP had a p-value of 2.0 × 10-8).
PMCID: PMC1866691  PMID: 16451704

Results 1-21 (21)