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1.  Genome-Wide Association Scan of Dupuytren's Disease 
The Journal of hand surgery  2010;35(12):2039-2045.
Purpose
Dupuytren's disease (DD) has strong genetic component that is suggested by population studies and family clustering. Genetic studies have yet to identify the gene(s) involved in DD. The purpose of this study was to identify regions of the entire genome (Chromosome 1 – 23) associated with the disease by performing a genome-wide association scan (GWAS) on DD patients and controls.
Methods
Genomic DNA (gDNA) was isolated from saliva collected from 40 unrelated DD patients and 40 unaffected controls. The genotyping was conducted using CytoSNP™ - Infinium® HD Ultra genotyping assay on the Illumina platform. The single nucleotides polymorphism (SNP) genotyping data was analyzed using both log regression and mapping by admixture linkage disequilibrium (MALD) analysis methods.
Results
The single SNP analysis revealed significant association in chromosomes 1, 3, 4, 5, 6, 11, 16, 17 and 23 regions. MALD analysis showed ancestry-associated regions in chromosomes 2, 6, 8, 11, 16 and 20, which may harbor DD susceptibility genes. Both analyses methods revealed loci association in chromosomes 6, 11 and 16.
Conclusions
Our data suggest that chromosome 6, 11 and 16 may contain the genes for DD and that multiple genes may be involved in DD. Future genetic studies on DD should focus on these areas of the genome.
doi:10.1016/j.jhsa.2010.08.008
PMCID: PMC2998563  PMID: 20971583
Dupuytren's disease; Dupuytren's disease genetics
2.  A Candidate Gene Study of Obstructive Sleep Apnea in European Americans and African Americans 
Rationale: Obstructive sleep apnea (OSA) is hypothesized to be influenced by genes within pathways involved with obesity, craniofacial development, inflammation, and ventilatory control.
Objectives: We conducted the first candidate gene study of OSA using family data from European Americans and African Americans, selecting biologically plausible genes from within these pathways.
Methods: A total of 1,080 single nucleotide polymorphisms (SNPs) were genotyped in 729 African Americans and 505 SNPs were genotyped in 694 European Americans. Coding for SNPs additively, association testing on the apnea-hypopnea index (AHI) as a continuous trait, and OSA as a dichotomous trait (AHI ≥15) was conducted using methods that account for familial correlations in models adjusted for age, age-squared, and sex, with and without body mass index.
Measurements and Main Results: In European Americans, variants within C-reactive protein (CRP) and glial cell line–derived neurotrophic factor (GDNF) were associated with AHI (CRP: β = 4.6; SE = 1.1; P = 0.0000402) (GDNF: β = 4.3; SE = 1; P = 0.0000201) and with the dichotomous OSA trait (CRP: odds ratio = 2.4; 95% confidence interval, 1.5–3.9; P = 0.000170) (GDNF: odds ratio = 2; 95% confidence interval, 1.4–2.89; P = 0.0000433). In African Americans, rs9526240 within serotonin receptor 2a (HTR2A: odds ratio = 2.1; 95% confidence interval, 1.5–2.9; P = 0.00005233) was associated with OSA.
Conclusions: This candidate gene analysis identified the potential role of genes operating through intermediate disease pathways to influence sleep apnea phenotypes, providing a framework for focusing future replication studies.
doi:10.1164/rccm.201002-0192OC
PMCID: PMC2970865  PMID: 20538960
sleep apnea; body mass index; genetics; candidate gene study
3.  A Genome-wide Admixture Scan for Ancestry-linked Genes Predisposing to Sarcoidosis in African Americans 
Genes and immunity  2010;12(2):67-77.
Genome-wide linkage and association studies have uncovered variants associated with sarcoidosis, a multi-organ granulomatous inflammatory disease. African ancestry may influence disease pathogenesis since African Americans are more commonly affected by sarcoidosis. Therefore, we conducted the first sarcoidosis genome-wide ancestry scan using a map of 1,384 highly ancestry informative single nucleotide polymorphisms genotyped on 1,357 sarcoidosis cases and 703 unaffected controls self-identified as African American. The most significant ancestry association was at marker rs11966463 on chromosome 6p22.3 (ancestry association risk ratio (aRR)= 1.90; p=0.0002). When we restricted the analysis to biopsy-confirmed cases, the aRR for this marker increased to 2.01; p=0.00007. Among the eight other markers that demonstrated suggestive ancestry associations with sarcoidosis were rs1462906 on chromosome 8p12 which had the most significant association with European ancestry (aRR=0.65; p=0.002), and markers on chromosomes 5p13 (aRR=1.46; p=0.005) and 5q31 (aRR=0.67; p=0.005), which correspond to regions we previously identified through sib pair linkage analyses. Overall, the most significant ancestry association for Scadding stage IV cases was to marker rs7919137 on chromosome 10p11.22 (aRR=0.27; p=2×10−5), a region not associated with disease susceptibility. In summary, through admixture mapping of sarcoidosis we have confirmed previous genetic linkages and identified several novel putative candidate loci for sarcoidosis.
doi:10.1038/gene.2010.56
PMCID: PMC3058725  PMID: 21179114
4.  Confirmation of Linkage to and Localization of Familial Colon Cancer Risk Haplotype on Chromosome 9q22 
Cancer research  2010;70(13):5409-5418.
Colorectal cancer is the second leading cause of cancer mortality in adult Americans and is caused by both genetic and environmental risk factors. We have replicated our originally reported linkage signal at 9q22-31 by fine mapping an independent collection of colon cancer families. Then, using a custom array of single nucleotide polymorphisms (SNPs) densely spaced across the candidate region, we performed both single-SNP and moving-window association analyses to identify a colon neoplasia risk haplotype. We isolated the association effect to a five SNP haplotype centered around 98.15 megabases (Mb) on chromosome 9q. This haplotype is in strong linkage disequilibrium with the haplotype block containing HABP4 and may be a surrogate for the effect of this CD30 Ki-1 antigen. It is also in close proximity to the GALNT12, which has been recently shown to be altered in colon tumors. Finally, we used a predictive modeling algorithm to demonstrate the contribution of this risk haplotype and surrounding candidate genes in distinguishing between colon cancer cases and healthy controls. The ability to replicate this finding, the strength of the haplotype association (OR=3.68) and the accuracy of our prediction model (~60%) all strongly support the presence of a locus for familial colon cancer on chromosome 9q.
doi:10.1158/0008-5472.CAN-10-0188
PMCID: PMC2896448  PMID: 20551049
colon cancer; linkage analysis; association analysis; risk; family cancer syndrome
5.  Genetic association tests: A method for the joint analysis of family and case-control data 
Human genomics  2009;4(1):2-20.
With the trend in molecular epidemiology towards both genome-wide association studies and complex modelling, the need for large sample sizes to detect small effects and to allow for the estimation of many parameters within a model continues to increase. Unfortunately, most methods of association analysis have been restricted to either a family-based or a case-control design, resulting in the lack of synthesis of data from multiple studies. Transmission disequilibrium-type methods for detecting linkage disequilibrium from family data were developed as an effective way of preventing the detection of association due to population stratification. Because these methods condition on parental genotype, however, they have precluded the joint analysis of family and case-control data, although methods for case-control data may not protect against population stratification and do not allow for familial correlations. We present here an extension of a family-based association analysis method for continuous traits that will simultaneously test for, and if necessary control for, population stratification. We further extend this method to analyse binary traits (and therefore family and case-control data together) and accurately to estimate genetic effects in the population, even when using an ascertained family sample. Finally, we present the power of this binary extension for both family-only and joint family and case-control data, and demonstrate the accuracy of the association parameter and variance components in an ascertained family sample.
PMCID: PMC2874328  PMID: 19951892
ascertainment correction; family-based association; linkage disequilibrium
6.  Triglyceride Levels and Not Adipokine Concentrations Are Closely Related to severity of Nonalcoholic Fatty Liver Disease in an Obesity surgery Cohort 
Obesity (Silver Spring, Md.)  2009;17(9):1696-1701.
Although nonalcoholic fatty liver disease (NAFLD) is frequent in obesity, the metabolic determinants of advanced liver disease remain unclear. Adipokines reflect inflammation and insulin resistance associated with obesity and may identify advanced NAFLD. At the time of obesity surgery, 142 consecutive patients underwent liver biopsy and had their preoperative demographic and clinical data obtained. Liver histology was scored by the NAFLD activity score, and patients subdivided into four groups. Concentrations of retinol-binding protein 4 (RBP4), adiponectin, tumor necrosis factor-α (TNF-α), and leptin were determined ~1 week prior to surgery and results were related to liver histology. The prevalence of no NAFLD was 30%, simple steatosis 23%, borderline nonalcoholic steatohepatitis (NASH) 28%, and definitive NASH 18%. Type 2 diabetes mellitus (T2DM) and metabolic syndrome (MS) prevalence were 39 and 75%, respectively, and did not differ across the four histological groups (P = NS). Triglyceride (TG) and alanine transaminase (ALT) levels, strongly associated with advanced stages of NAFLD and NASH (P = 0.04). TG levels >150 mg/dl, increased the likelihood of NASH 3.4-fold, whereas high-density lipoprotein (HDL) levels predicted no NAFLD (P < 0.01). Concentrations of TNF-α, leptin, and RBP4 did not differ among histological groups and thus did not identify NASH; however, there was a trend for adiponectin to be lower in NASH vs. no NAFLD (P = 0.061). In summary, both TG and ALT levels assist in identification of NASH in an obesity surgery cohort. These findings underscore the importance of fatty acid delivery mechanisms to NASH development in severely obese individuals.
doi:10.1038/oby.2009.89
PMCID: PMC2829436  PMID: 19360015
7.  Evaluation of C1q genomic region in minority racial groups of lupus 
Genes and immunity  2009;10(5):517-524.
Complement cascade plasma proteins have a complex role in the etiopathogenesis of SLE. Hereditary C1q deficiency has been strongly related to SLE; however, there are very few published SLE studies that evaluate the polymorphisms of the genes encoding for C1q (A, B, and C). In this study, we evaluated 17 single nucleotide polymorphisms (SNPs) across 37 kb of C1QA, B and C in a lupus cohort of peoples of African-American and Hispanic origin. In a case only analysis, significant association at multiple SNPs in the C1QA gene was detected in African-Americans with kidney nephritis (best p=4.91 × 10−6). In addition, C1QA was associated with SLE in African-Americans with a lack of nephritis and accompanying photosensitivity when compared to normal controls (p=6.80 × 10−6). A similar trend was observed in the Hispanic subjects (p=0.003). Quantitative analysis demonstrates that some SNPs in the C1q genes might be correlated with C3 complement levels in an additive model among African-Americans (best p=0.0001). The CIQA gene is associated with subphenotypes of lupus in African-American and Hispanic subjects. Further studies with higher SNP densities in this region and other complement components are necessary to elucidate the complex genetics and phenotypic interactions between complement components and SLE.
doi:10.1038/gene.2009.33
PMCID: PMC2769492  PMID: 19440201
8.  Meta-analysis and Imputation Identifies a 109 kb Risk Haplotype Spanning TNFAIP3 Associated with Lupus Nephritis and Hematologic Manifestations 
Genes and immunity  2009;10(5):470-477.
TNFAIP3 encodes the ubiquitin modifying enzyme, A20, a key regulator of inflammatory signaling pathways. We previously reported association between TNFAIP3 variants and systemic lupus erythematosus (SLE). In order to further localize the risk variant(s), we performed a meta-analysis using genetic data available from two Caucasian case/control datasets (1453 total cases, 3381 total controls) and 713 SLE trio families. The best result was found at rs5029939 (P = 1.67 × 10−14, OR = 2.09, 95% CI 1.68–2.60). We then imputed SNPs from the CEU Phase II HapMap using genotypes from 431 SLE cases and 2155 controls. Imputation identified eleven SNPs in addition to three observed SNPs, which together, defined a 109 kb SLE risk segment surrounding TNFAIP3. When evaluating whether the rs5029939 risk allele was associated with SLE clinical manifestations, we observed that heterozygous carriers of the TNFAIP3 risk allele at rs5029939 have a two-fold increased risk of developing renal or hematologic manifestations compared to homozygous non-risk subjects. In summary, our study strengthens the genetic evidence that variants in the region of TNFAIP3 influence risk for SLE, particularly in patients with renal and hematologic manifestations, and narrows the risk effect to a 109 kb DNA segment that spans the TNFAIP3 gene.
doi:10.1038/gene.2009.31
PMCID: PMC2714405  PMID: 19387456
systemic lupus erythematosus; TNFAIP3; imputation; meta-analysis
9.  Comparison of univariate and multivariate linkage analysis of traits related to hypertension 
BMC Proceedings  2009;3(Suppl 7):S99.
Complex traits are often manifested by multiple correlated traits. One example of this is hypertension (HTN), which is measured on a continuous scale by systolic blood pressure (SBP). Predisposition to HTN is predicted by hyperlipidemia, characterized by elevated triglycerides (TG), low-density lipids (LDL), and high-density lipids (HDL). We hypothesized that the multivariate analysis of TG, LDL, and HDL would be more powerful for detecting HTN genes via linkage analysis compared with univariate analysis of SBP. We conducted linkage analysis of four chromosomal regions known to contain genes associated with HTN using SBP as a measure of HTN in univariate Haseman-Elston regression and using the correlated traits TG, LDL, and HDL in multivariate Haseman-Elston regression. All analyses were conducted using the Framingham Heart Study data. We found that multivariate linkage analysis was better able to detect chromosomal regions in which the angiotensinogen, angiotensin receptor, guanine nucleotide-binding protein 3, and prostaglandin I2 synthase genes reside. Univariate linkage analysis only detected the AGT gene. We conclude that multivariate analysis is appropriate for the analysis of multiple correlated phenotypes, and our findings suggest that it may yield new linkage signals undetected by univariate analysis.
PMCID: PMC2796003  PMID: 20018096
10.  Defining genetic determinants of the Metabolic Syndrome in the Framingham Heart Study using association and structural equation modeling methods 
BMC Proceedings  2009;3(Suppl 7):S50.
The Metabolic Syndrome (MetSyn), which is a clustering of traits including insulin resistance, obesity, hypertension and dyslipidemia, is estimated to have a substantial genetic component, yet few specific genetic targets have been identified. Factor analysis, a sub-type of structural equation modeling (SEM), has been used to model the complex relationships in MetSyn. Therefore, we aimed to define the genetic determinants of MetSyn in the Framingham Heart Study (Offspring Cohort, Exam 7) using the Affymetrix 50 k Human Gene Panel and three different approaches: 1) an association-based "one-SNP-at-a-time" analysis with MetSyn as a binary trait using the World Health Organization criteria; 2) an association-based "one-SNP-at-a-time" analysis with MetSyn as a continuous trait using second-order factor scores derived from four first-order factors; and, 3) a multivariate SEM analysis with MetSyn as a continuous, second-order factor modeled with multiple putative genes, which were represented by latent constructs defined using multiple SNPs in each gene. Results were similar between approaches in that CSMD1 SNPs were associated with MetSyn in Approaches 1 and 2; however, the effects of CSMD1 diminished in Approach 3 when modeled simultaneously with six other genes, most notably CETP and STARD13, which were strongly associated with the Lipids and MetSyn factors, respectively. We conclude that modeling multiple genes as latent constructs on first-order trait factors, most proximal to the gene's function with limited paths directly from genes to the second-order MetSyn factor, using SEM is the most viable approach toward understanding overall gene variation effects in the presence of multiple putative SNPs.
PMCID: PMC2795950  PMID: 20018043
11.  Mendelian randomization in family data 
BMC Proceedings  2009;3(Suppl 7):S45.
The phrase "mendelian randomization" has become associated with the use of genetic polymorphisms to uncover causal relationships between phenotypic variables. The statistical methods useful in mendelian randomization are known as instrumental variable techniques. We present an approach to instrumental variable estimation that is useful in family data and is robust to the use of weak instruments. We illustrate our method to measure the causal influence of low-density lipoprotein on high-density lipoprotein, body mass index, triglycerides, and systolic blood pressure. We use the Framingham Heart Study data as distributed to participants in the Genetics Analysis Workshop 16.
PMCID: PMC2795944  PMID: 20018037
12.  Multivariate association analysis of the components of metabolic syndrome from the Framingham Heart Study 
BMC Proceedings  2009;3(Suppl 7):S42.
Metabolic syndrome, by definition, is the manifestation of multiple, correlated metabolic impairments. It is known to have both strong environmental and genetic contributions. However, isolating genetic variants predisposing to such a complex trait has limitations. Using pedigree data, when available, may well lead to increased ability to detect variants associated with such complex traits. The ability to incorporate multiple correlated traits into a joint analysis may also allow increased detection of associated genes. Therefore, to demonstrate the utility of both univariate and multivariate family-based association analysis and to identify possible genetic variants associated with metabolic syndrome, we performed a scan of the Affymetrix 50 k Human Gene Panel data using 1) each of the traits comprising metabolic syndrome: triglycerides, high-density lipoprotein, systolic blood pressure, diastolic blood pressure, blood glucose, and body mass index, and 2) a composite trait including all of the above, jointly. Two single-nucleotide polymorphisms within the cholesterol ester transfer protein (CETP) gene remained significant even after correcting for multiple testing in both the univariate (p < 5 × 10-7) and multivariate (p < 5 × 10-9) association analysis. Three genes met significance for multiple traits after correction for multiple testing in the univariate analysis, while five genes remained significant in the multivariate association. We conclude that while both univariate and multivariate family-based association analysis can identify genes of interest, our multivariate approach is less affected by multiple testing correction and yields more significant results.
PMCID: PMC2795941  PMID: 20018034
13.  Genetic association tests: a method for the joint analysis of family and case-control data 
Human Genomics  2009;4(1):2-20.
With the trend in molecular epidemiology towards both genome-wide association studies and complex modelling, the need for large sample sizes to detect small effects and to allow for the estimation of many parameters within a model continues to increase. Unfortunately, most methods of association analysis have been restricted to either a family-based or a case-control design, resulting in the lack of synthesis of data from multiple studies. Transmission disequilibrium-type methods for detecting linkage disequilibrium from family data were developed as an effective way of preventing the detection of association due to population stratification. Because these methods condition on parental genotype, however, they have precluded the joint analysis of family and case-control data, although methods for case-control data may not protect against population stratification and do not allow for familial correlations. We present here an extension of a family-based association analysis method for continuous traits that will simultaneously test for, and if necessary control for, population stratification. We further extend this method to analyse binary traits (and therefore family and case-control data together) and accurately to estimate genetic effects in the population, even when using an ascertained family sample. Finally, we present the power of this binary extension for both family-only and joint family and case-control data, and demonstrate the accuracy of the association parameter and variance components in an ascertained family sample.
doi:10.1186/1479-7364-4-1-2
PMCID: PMC2874328  PMID: 19951892
ascertainment correction; family-based association; linkage disequilibrium
14.  Haseman Elston Regression in Ascertained Samples: Importance of Dependent Variable and Mean Correction Factor Selection 
Human Heredity  2007;65(2):66-76.
Objective
One of the first tools for performing linkage analysis, Haseman-Elston regression (HE), has been successfully used to identify linkages to several disease traits. A recent explosion in extensions of HE leaves one faced with the task of choosing a flavor of HE best suited for a given situation. This paper puts this dilemma into perspective and proposes a modification to HE for highly ascertained samples (BLUP-PM).
Methods
Using data simulated for a range of models, we evaluated type I error and power of several dependent variables in HE, including the novel BLUP-PM.
Results
When analyzing a continuous trait, even in highly ascertained samples, type I error is stable and approximately nominal across dependent variables. When analyzing binary traits in highly ascertained samples, type I error is elevated and unstable for all except BLUP-PM. Regardless of trait type, the optimally weighted HE regression and BLUP-PM have the greatest power.
Conclusions
Ascertained samples do not always reflect the population from which they are drawn and therefore choice of dependent variable in HE becomes increasingly important. Our results do not reveal a single, universal choice, but offer criteria by which to choose and demonstrate BLUP-PM performs well in most situations.
doi:10.1159/000108938
PMCID: PMC2857627  PMID: 17898537
Haseman-Elston regression; Linkage; Ascertainment
15.  Effect of genotyping error in model-free linkage analysis using microsatellite or single-nucleotide polymorphism marker maps 
BMC Genetics  2005;6(Suppl 1):S153.
Errors while genotyping are inevitable and can reduce the power to detect linkage. However, does genotyping error have the same impact on linkage results for single-nucleotide polymorphism (SNP) and microsatellite (MS) marker maps? To evaluate this question we detected genotyping errors that are consistent with Mendelian inheritance using large changes in multipoint identity-by-descent sharing in neighboring markers. Only a small fraction of Mendelian consistent errors were detectable (e.g., 18% of MS and 2.4% of SNP genotyping errors). More SNP genotyping errors are Mendelian consistent compared to MS genotyping errors, so genotyping error may have a greater impact on linkage results using SNP marker maps. We also evaluated the effect of genotyping error on the power and type I error rate using simulated nuclear families with missing parents under 0, 0.14, and 2.8% genotyping error rates. In the presence of genotyping error, we found that the power to detect a true linkage signal was greater for SNP (75%) than MS (67%) marker maps, although there were also slightly more false-positive signals using SNP marker maps (5 compared with 3 for MS). Finally, we evaluated the usefulness of accounting for genotyping error in the SNP data using a likelihood-based approach, which restores some of the power that is lost when genotyping error is introduced.
doi:10.1186/1471-2156-6-S1-S153
PMCID: PMC1866781  PMID: 16451614
16.  A regression based transmission/disequilibrium test for binary traits: the power of joint tests for linkage and association 
BMC Genetics  2005;6(Suppl 1):S95.
Background
In this analysis we applied a regression based transmission disequilibrium test to the binary trait presence or absence of Kofendred Personality Disorder in the Genetic Analysis Workshop 14 (GAW14) simulated dataset and determined the power and type I error rate of the method at varying map densities and sample sizes. To conduct this transmission disequilibrium test, the logit transformation was applied to a binary outcome and regressed on an indicator variable for the transmitted allele from informative matings. All 100 replicates from chromosomes 1, 3, 5, and 9 for the Aipotu and the combined Aipotu, Karangar, and Danacaa populations were used at densities of 3, 1, and 0.3 cM. Power and type I error were determined by the number of replicates significant at the 0.05 level.
Results
The maximum power to detect linkage and association with the Aipotu population was 93% for chromosome 3 using a 0.3-cM map. For chromosomes 1, 5, and 9 the power was less than 10% at the 3-cM scan and less than 22% for the 0.3-cM map. With the larger sample size, power increased to 38% for chromosome 1, 100% for chromosome 3, 31% for chromosome 5, and 23% for chromosome 9. Type I error was approximately 7%.
Conclusion
The power of this method is highly dependent on the amount of information in a region. This study suggests that single-point methods are not particularly effective in narrowing a fine-mapping region, particularly when using single-nucleotide polymorphism data and when linkage disequilibrium in the region is variable.
doi:10.1186/1471-2156-6-S1-S95
PMCID: PMC1866684  PMID: 16451711
18.  A review of the 'Statistical Analysis for Genetic Epidemiology' (SAGE) software package 
Human Genomics  2004;1(6):456-459.
The 'Statistical Analysis for Genetic Epidemiology' (S.A.G.E.) software package is an integrated, comprehensive package of computer programs designed to perform many of the different analyses required in the study of genetic epidemiology. It offers a graphical user interface for most platforms and, unlike many programs available in the public domain, is flexible in both receiving many types of input files and in allowing the user to choose among output files. All of the programs accept the same data files and together provide the means to perform familial correlation, segregation, linkage and association analyses, as well as many of the ancillary analyses that help achieve these goals. Many, but not all, of the same or similar analyses can be performed (with more difficulty) using publicly available freeware. The primary limitations of S.A.G.E. at present are the lack of software for estimating haplotypes or for identifying probable double recombinants in linkage analysis. S.A.G.E. is continually being extended and upgraded, however, with automatic downloading of the latest version always available to users.
doi:10.1186/1479-7364-1-6-456
PMCID: PMC3500199  PMID: 15607000
familial correlations; segregation; linkage and association analyses; heritability; transmission disequilibrium test; allele frequency
19.  Genome-wide linkage scan for genes affecting longitudinal trends in systolic blood pressure 
BMC Genetics  2003;4(Suppl 1):S82.
Only one genome scan to date has attempted to make use of the longitudinal data available in the Framingham Heart Study, and this attempt yielded evidence of linkage to a gene for mean systolic blood pressure. We show how the additional information available in these longitudinal data can be utilized to examine linkages for not only mean systolic blood pressure (SBP), but also for its trend with age and its variability. Prior to linkage analysis, individuals treated for hypertension were adjusted to account for right-censoring of SBP. Regressions on age were fitted to obtain orthogonal measures of slope, curvature, and residual variance of SBP that were then used as dependent variables in the model-free linkage program SIBPAL. We included mean age, gender, and cohort as covariates in the analysis. To improve power, sibling pairs were weighted for informativity using weights derived from both the marker and trait. The most significant results from our analyses were found on chromosomes 12, 15, and 17 for mean SBP, and chromosome 20 for both SBP slope and curvature.
doi:10.1186/1471-2156-4-S1-S82
PMCID: PMC1866522  PMID: 14975150

Results 1-19 (19)