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1.  Genome-wide association of echocardiographic dimensions, brachial artery endothelial function and treadmill exercise responses in the Framingham Heart Study 
BMC Medical Genetics  2007;8(Suppl 1):S2.
Echocardiographic left ventricular (LV) measurements, exercise responses to standardized treadmill test (ETT) and brachial artery (BA) vascular function are heritable traits that are associated with cardiovascular disease risk. We conducted a genome-wide association study (GWAS) in the community-based Framingham Heart Study.
We estimated multivariable-adjusted residuals for quantitative echocardiography, ETT and BA function traits. Echocardiography residuals were averaged across 4 examinations and included LV mass, diastolic and systolic dimensions, wall thickness, fractional shortening, left atrial and aortic root size. ETT measures (single exam) included systolic blood pressure and heart rate responses during exercise stage 2, and at 3 minutes post-exercise. BA measures (single exam) included vessel diameter, flow-mediated dilation (FMD), and baseline and hyperemic flow responses. Generalized estimating equations (GEE), family-based association tests (FBAT) and variance-components linkage were used to relate multivariable-adjusted trait residuals to 70,987 SNPs (Human 100K GeneChip, Affymetrix) restricted to autosomal SNPs with minor allele frequency ≥0.10, genotype call rate ≥0.80, and Hardy-Weinberg equilibrium p ≥ 0.001.
We summarize results from 17 traits in up to 1238 related middle-aged to elderly men and women. Results of all association and linkage analyses are web-posted at . We confirmed modest-to-strong heritabilities (estimates 0.30–0.52) for several Echo, ETT and BA function traits. Overall, p < 10-5 in either GEE or FBAT models were observed for 21 SNPs (nine for echocardiography, eleven for ETT and one for BA function). The top SNPs associated were (GEE results): LV diastolic dimension, rs1379659 (SLIT2, p = 1.17*10-7); LV systolic dimension, rs10504543 (KCNB2, p = 5.18*10-6); LV mass, rs10498091 (p = 5.68*10-6); Left atrial size, rs1935881 (FAM5C, p = 6.56*10-6); exercise heart rate, rs6847149 (NOLA1, p = 2.74*10-6); exercise systolic blood pressure, rs2553268 (WRN, p = 6.3*10-6); BA baseline flow, rs3814219 (OBFC1, 9.48*10-7), and FMD, rs4148686 (CFTR, p = 1.13*10-5). Several SNPs are reasonable biological candidates, with some being related to multiple traits suggesting pleiotropy. The peak LOD score was for LV mass (4.38; chromosome 5); the 1.5 LOD support interval included NRG2.
In hypothesis-generating GWAS of echocardiography, ETT and BA vascular function in a moderate-sized community-based sample, we identified several SNPs that are candidates for replication attempts and we provide a web-based GWAS resource for the research community.
PMCID: PMC1995617  PMID: 17903301
2.  Power comparison between population-based case–control studies and family-based transmission–disequilibrium tests: An empirical study 
Indian Journal of Human Genetics  2011;17(Suppl 1):S27-S31.
There are two major classes of genetic association analyses: population based and family based. Population-based case–control studies have been the method of choice due to the ease of data collection. However, population stratification is one of the major limitations of case–control studies, while family-based studies are protected against stratification. In this study, we carry out extensive simulations under different disease models (both Mendelian as well as complex) to evaluate the relative powers of the two approaches in detecting association.
The power comparisons are based on a case–control design comprising 200 cases and 200 controls versus a Transmission Disequilibrium Test (TDT) or Pedigree Disequilibrium Test (PDT) design with 200 informative trios. We perform the allele-level test for case–control studies, which is based on the difference of allele frequencies at a single nucleotide polymorphism (SNP) between unrelated cases and controls. The TDT and the PDT are based on preferential allelic transmissions at a SNP from heterozygous parents to the affected offspring. We considered five disease modes of inheritance: (i) recessive with complete penetrance (ii) dominant with complete penetrance and (iii), (iv) and (v) complex diseases with varying levels of penetrances and phenocopies.
We find that while the TDT/PDT design with 200 informative trios is in general more powerful than a case–control design with 200 cases and 200 controls (except when the heterozygosity at the marker locus is high), it may be necessary to sample a very large number of trios to obtain the requisite number of informative families.
The current study provides insights into power comparisons between population-based and family-based association studies.
PMCID: PMC3125051  PMID: 21747584
Allelic association; informative trios; complex genetic disorder
3.  A family-based association test to detect gene–gene interactions in the presence of linkage 
For many complex diseases, quantitative traits contain more information than dichotomous traits. One of the approaches used to analyse these traits in family-based association studies is the quantitative transmission disequilibrium test (QTDT). The QTDT is a regression-based approach that models simultaneously linkage and association. It splits up the association effect in a between- and a within-family genetic component to adjust and test for population stratification and includes a variance components method to model linkage. We extend this approach to detect gene–gene interactions between two unlinked QTLs by adjusting the definition of the between- and within-family component and the variance components included in the model. We simulate data to investigate the influence of the epistasis model, linkage disequilibrium patterns between the markers and the QTLs, and allele frequencies on the power and type I error rates of the approach. Results show that for some of the investigated settings, power gains are obtained in comparison with FAM-MDR. We conclude that our approach shows promising results for candidate-gene studies where too few markers are available to correct for population stratification using standard methods (for example EIGENSTRAT). The proposed method is applied to real-life data on hypertension from the FLEMENGHO study.
PMCID: PMC3421128  PMID: 22419171
QTDT; epistasis; association; linkage
4.  Transmission/Disequilibrium Tests Incorporating Unaffected Offspring 
PLoS ONE  2014;9(12):e114892.
We propose a new method for family-based tests of association and linkage called transmission/disequilibrium tests incorporating unaffected offspring (TDTU). This new approach, constructed based on transmission/disequilibrium tests for quantitative traits (QTDT), provides a natural extension of the transmission/disequilibrium test (TDT) to utilize transmission information from heterozygous parents to their unaffected offspring as well as the affected offspring from ascertained nuclear families. TDTU can be used in various study designs and can accommodate all types of independent nuclear families with at least one affected offspring. When the study sample contains only case-parent trios, the TDTU is equivalent to TDT. Informative-transmission disequilibrium test (i-TDT) and generalized disequilibrium test(GDT) are another two methods that can use information of both unaffected offspring and affected offspring. In contract to i-TDT and GDT, the test statistic of TDTU is simpler and more explicit, and can be implemented more easily. Through computer simulations, we demonstrate that power of the TDTU is slightly higher compared to i-TDT and GDT. All the three methods are more powerful than method that uses affected offspring only, suggesting that unaffected siblings also provide information about linkage and association.
PMCID: PMC4275232  PMID: 25535968
5.  TDT-HET: A new transmission disequilibrium test that incorporates locus heterogeneity into the analysis of family-based association data 
BMC Bioinformatics  2012;13:13.
Locus heterogeneity is one of the most documented phenomena in genetics. To date, relatively little work had been done on the development of methods to address locus heterogeneity in genetic association analysis. Motivated by Zhou and Pan's work, we present a mixture model of linked and unlinked trios and develop a statistical method to estimate the probability that a heterozygous parent transmits the disease allele at a di-allelic locus, and the probability that any trio is in the linked group. The purpose here is the development of a test that extends the classic transmission disequilibrium test (TDT) to one that accounts for locus heterogeneity.
Our simulations suggest that, for sufficiently large sample size (1000 trios) our method has good power to detect association even the proportion of unlinked trios is high (75%). While the median difference (TDT-HET empirical power - TDT empirical power) is approximately 0 for all MOI, there are parameter settings for which the power difference can be substantial. Our multi-locus simulations suggest that our method has good power to detect association as long as the markers are reasonably well-correlated and the genotype relative risk are larger. Results of both single-locus and multi-locus simulations suggest our method maintains the correct type I error rate.
Finally, the TDT-HET statistic shows highly significant p-values for most of the idiopathic scoliosis candidate loci, and for some loci, the estimated proportion of unlinked trios approaches or exceeds 50%, suggesting the presence of locus heterogeneity.
We have developed an extension of the TDT statistic (TDT-HET) that allows for locus heterogeneity among coded trios. Benefits of our method include: estimates of parameters in the presence of heterogeneity, and reasonable power even when the proportion of linked trios is small. Also, we have extended multi-locus methods to TDT-HET and have demonstrated that the empirical power may be high to detect linkage. Last, given that we obtain PPBs, we conjecture that the TDT-HET may be a useful method for correctly identifying linked trios. We anticipate that researchers will find this property increasingly useful as they apply next-generation sequencing data in family based studies.
PMCID: PMC3292499  PMID: 22264315
6.  Sequence Kernel Association Test for Quantitative Traits in Family Samples 
Genetic epidemiology  2012;37(2):196-204.
A large number of rare genetic variants have been discovered with the development in sequencing technology and the lowering of sequencing costs. Rare variant analysis may help identify novel genes associated with diseases and quantitative traits, adding to our knowledge of explaining heritability of these phenotypes. Many statistical methods for rare variant analysis have been developed in recent years, but some of them require the strong assumption that all rare variants in the analysis share the same direction of effect, and others requiring permutation to calculate the p-values are computer intensive. Among these methods, the sequence kernel association test (SKAT) is a powerful method under many different scenarios. It does not require any assumption on the directionality of effects, and statistical significance is computed analytically. In this paper, we extend SKAT to be applicable to family data. The family-based SKAT (famSKAT) has a different test statistic and null distribution compared to SKAT, but is equivalent to SKAT when there is no familial correlation. Our simulation studies show that SKAT has inflated type I error if familial correlation is inappropriately ignored, but has appropriate type I error if applied to a single individual per family to obtain an unrelated subset. In the contrast, famSKAT has the correct type I error when analyzing correlated observations, and it has higher power than competing methods in many different scenarios. We illustrate our approach to analyze the association of rare genetic variants using glycemic traits from the Framingham Heart Study.
PMCID: PMC3642218  PMID: 23280576
rare variant analysis; quantitative traits; family samples; heritability; linear mixed effects model
7.  FAM-MDR: A Flexible Family-Based Multifactor Dimensionality Reduction Technique to Detect Epistasis Using Related Individuals 
PLoS ONE  2010;5(4):e10304.
We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.
PMCID: PMC2858665  PMID: 20421984
8.  A novel approach for haplotype-based association analysis using family data 
BMC Bioinformatics  2010;11(Suppl 1):S45.
Haplotype-based approaches have been extensively studied for case-control association mapping in recent years. It has been shown that haplotype methods can provide more consistent results comparing to single-locus based approaches, especially in cases where causal variants are not typed. Improved power has been observed by clustering similar or rare haplotypes into groups to reduce the degrees of freedom of association tests. For family-based association studies, one commonly used strategy is Transmission Disequilibrium Tests (TDT), which examine the imbalanced transmission of alleles/haplotypes to affected and normal children. Many extensions have been developed to deal with general pedigrees and continuous traits.
In this paper, we propose a new haplotype-based association method for family data that is different from the TDT framework. Our approach (termed F_HapMiner) is based on our previous successful experiences on haplotype inference from pedigree data and haplotype-based association mapping. It first infers diplotype pairs of each individual in each pedigree assuming no recombination within a family. A phenotype score is then defined for each founder haplotype. Finally, F_HapMiner applies a clustering algorithm on those founder haplotypes based on their similarities and identifies haplotype clusters that show significant associations with diseases/traits. We have performed extensive simulations based on realistic assumptions to evaluate the effectiveness of the proposed approach by considering different factors such as allele frequency, linkage disequilibrium (LD) structure, disease model and sample size. Comparisons with single-locus and haplotype-based TDT methods demonstrate that our approach consistently outperforms the TDT-based approaches regardless of disease models, local LD structures or allele/haplotype frequencies.
We present a novel haplotype-based association approach using family data. Experiment results demonstrate that it achieves significantly higher power than TDT-based approaches.
PMCID: PMC3009518  PMID: 20122219
9.  A new transmission test for affected sib-pair families 
BMC Proceedings  2007;1(Suppl 1):S32.
Family-based association approaches such as the transmission-disequilibrium test (TDT) are used extensively in the study of genetic traits because they are generally robust to the presence of population structure. However, these approaches necessarily involve recruitment of families, which is more costly and time-consuming than sampling unrelated individuals in the population-based approaches. Therefore, a family-based approach, which has high power, would be appealing because of the gain in time and cost due to the reduced sample size that is required to attain adequate power. Here we introduce a new family-based transmission test using the joint transmission status from affected sib pairs. We show that by including the transmission status of both siblings, our method gives higher power than the TDT design, while maintaining the correct type I error rate. We use the simulated data from affected sib-pair families with rheumatoid arthritis provided by Genetic Analysis Workshop 15 to illustrate our approach.
PMCID: PMC2367567  PMID: 18466530
10.  A Review of Family-Based Tests for Linkage Disequilibrium between a Quantitative Trait and a Genetic Marker 
PLoS Genetics  2008;4(9):e1000180.
Quantitative trait transmission/disequilibrium tests (quantitative TDTs) are commonly used in family-based genetic association studies of quantitative traits. Despite the availability of various quantitative TDTs, some users are not aware of the properties of these tests and the relationships between them. This review aims at outlining the broad features of the various quantitative TDT procedures carried out in the frequently used QTDT and FBAT packages. Specifically, we discuss the “Rabinowitz” and the “Monks-Kaplan” procedures, as well as the various “Abecasis” and “Allison” regression-based procedures. We focus on the models assumed in these tests and the relationships between them. Moreover, we discuss what hypotheses are tested by the various quantitative TDTs, what testing procedures are best suited to various forms of data, and whether the regression-based tests overcome population stratification problems. Finally, we comment on power considerations in the choice of the test to be used. We hope this brief review will shed light on the similarities and differences of the various quantitative TDTs.
PMCID: PMC2528965  PMID: 18818728
11.  Genetic and functional association of FAM5C with myocardial infarction 
BMC Medical Genetics  2008;9:33.
We previously identified a 40 Mb region of linkage on chromosome 1q in our early onset coronary artery disease (CAD) genome-wide linkage scan (GENECARD) with modest evidence for linkage (n = 420, LOD 0.95). When the data are stratified by acute coronary syndrome (ACS), this modest maximum in the overall group became a well-defined LOD peak (maximum LOD of 2.17, D1S1589/D1S518). This peak overlaps a recently identified inflammatory biomarker (MCP-1) linkage region from the Framingham Heart Study (maximum LOD of 4.27, D1S1589) and a region of linkage to metabolic syndrome from the IRAS study (maximum LOD of 2.59, D1S1589/D1S518). The overlap of genetic screens in independent data sets provides evidence for the existence of a gene or genes for CAD in this region.
A peak-wide association screen (457 SNPs) was conducted of a region 1 LOD score down from the peak marker (168–198 Mb) in a linkage peak for acute coronary syndrome (ACS) on chromosome 1, within a family-based early onset coronary artery disease (CAD) sample (GENECARD).
Polymorphisms were identified within the 'family with sequence similarity 5, member C' gene (FAM5C) that show genetic linkage to and are associated with myocardial infarction (MI) in GENECARD. The association was confirmed in an independent CAD case-control sample (CATHGEN) and strong association with MI was identified with single nucleotide polymorphisms (SNPs) in the 3' end of FAM5C. FAM5C genotypes were also correlated with expression of the gene in human aorta. Expression levels of FAM5C decreased with increasing passage of proliferating aortic smooth muscle cells (SMC) suggesting a role for this molecule in smooth muscle cell proliferation and senescence.
These data implicate FAM5C alleles in the risk of myocardial infarction and suggest further functional studies of FAM5C are required to identify the gene's contribution to atherosclerosis.
PMCID: PMC2383879  PMID: 18430236
12.  Screening and Replication using the Same Data Set: Testing Strategies for Family-Based Studies in which All Probands Are Affected 
PLoS Genetics  2008;4(9):e1000197.
For genome-wide association studies in family-based designs, we propose a powerful two-stage testing strategy that can be applied in situations in which parent-offspring trio data are available and all offspring are affected with the trait or disease under study. In the first step of the testing strategy, we construct estimators of genetic effect size in the completely ascertained sample of affected offspring and their parents that are statistically independent of the family-based association/transmission disequilibrium tests (FBATs/TDTs) that are calculated in the second step of the testing strategy. For each marker, the genetic effect is estimated (without requiring an estimate of the SNP allele frequency) and the conditional power of the corresponding FBAT/TDT is computed. Based on the power estimates, a weighted Bonferroni procedure assigns an individually adjusted significance level to each SNP. In the second stage, the SNPs are tested with the FBAT/TDT statistic at the individually adjusted significance levels. Using simulation studies for scenarios with up to 1,000,000 SNPs, varying allele frequencies and genetic effect sizes, the power of the strategy is compared with standard methodology (e.g., FBATs/TDTs with Bonferroni correction). In all considered situations, the proposed testing strategy demonstrates substantial power increases over the standard approach, even when the true genetic model is unknown and must be selected based on the conditional power estimates. The practical relevance of our methodology is illustrated by an application to a genome-wide association study for childhood asthma, in which we detect two markers meeting genome-wide significance that would not have been detected using standard methodology.
Author Summary
The current state of genotyping technology has enabled researchers to conduct genome-wide association studies of up to 1,000,000 SNPs, allowing for systematic scanning of the genome for variants that might influence the development and progression of complex diseases. One of the largest obstacles to the successful detection of such variants is the multiple comparisons/testing problem in the genetic association analysis. For family-based designs in which all offspring are affected with the disease/trait under study, we developed a methodology that addresses this problem by partitioning the family-based data into two statistically independent components. The first component is used to screen the data and determine the most promising SNPs. The second component is used to test the SNPs for association, where information from the screening is used to weight the SNPs during testing. This methodology is more powerful than standard procedures for multiple comparisons adjustment (i.e., Bonferroni correction). Additionally, as only one data set is required for screening and testing, our testing strategy is less susceptible to study heterogeneity. Finally, as many family-based studies collect data only from affected offspring, this method addresses a major limitation of previous methodologies for multiple comparisons in family-based designs, which require variation in the disease/trait among offspring.
PMCID: PMC2529406  PMID: 18802462
13.  Tests of Association for Quantitative Traits in Nuclear Families Using Principal Components to Correct for Population Stratification 
Annals of human genetics  2009;73(Pt 6):601-613.
Traditional transmission disequilibrium test (TDT) based methods for genetic association analyses are robust to population stratification at the cost of a substantial loss of power. We here describe a novel method for family-based association studies that corrects for population stratification with the use of an extension of principal component analysis (PCA). Specifically, we adopt PCA on unrelated parents in each family. We then infer principal components for children from those for their parents through a TDT-like strategy. Two test statistics within variance-components model are proposed for association tests. Simulation results show that the proposed tests have correct type I error rates regardless of population stratification, and have greatly improved power over two popular TDT-based methods: QTDT and FBAT. The application to the Genetic Analysis Workshop 16 (GAW16) data sets attests to the feasibility of the proposed method.
PMCID: PMC2764806  PMID: 19702646
Family Based Association Tests (FBATs); Transmission Disequilibrium Test (TDT); Principal Component Analysis (PCA); Variance-Components
14.  Inactivation of a Novel FGF23 Regulator, FAM20C, Leads to Hypophosphatemic Rickets in Mice 
PLoS Genetics  2012;8(5):e1002708.
Family with sequence similarity 20,-member C (FAM20C) is highly expressed in the mineralized tissues of mammals. Genetic studies showed that the loss-of-function mutations in FAM20C were associated with human lethal osteosclerotic bone dysplasia (Raine Syndrome), implying an inhibitory role of this molecule in bone formation. However, in vitro gain- and loss-of-function studies suggested that FAM20C promotes the differentiation and mineralization of mouse mesenchymal cells and odontoblasts. Recently, we generated Fam20c conditional knockout (cKO) mice in which Fam20c was globally inactivated (by crossbreeding with Sox2-Cre mice) or inactivated specifically in the mineralized tissues (by crossbreeding with 3.6 kb Col 1a1-Cre mice). Fam20c transgenic mice were also generated and crossbred with Fam20c cKO mice to introduce the transgene in the knockout background. In vitro gain- and loss-of-function were examined by adding recombinant FAM20C to MC3T3-E1 cells and by lentiviral shRNA–mediated knockdown of FAM20C in human and mouse osteogenic cell lines. Surprisingly, both the global and mineralized tissue-specific cKO mice developed hypophosphatemic rickets (but not osteosclerosis), along with a significant downregulation of osteoblast differentiation markers and a dramatic elevation of fibroblast growth factor 23 (FGF23) in the serum and bone. The mice expressing the Fam20c transgene in the wild-type background showed no abnormalities, while the expression of the Fam20c transgene fully rescued the skeletal defects in the cKO mice. Recombinant FAM20C promoted the differentiation and mineralization of MC3T3-E1 cells. Knockdown of FAM20C led to a remarkable downregulation of DMP1, along with a significant upregulation of FGF23 in both human and mouse osteogenic cell lines. These results indicate that FAM20C is a bone formation “promoter” but not an “inhibitor” in mouse osteogenesis. We conclude that FAM20C may regulate osteogenesis through its direct role in facilitating osteoblast differentiation and its systemic regulation of phosphate homeostasis via the mediation of FGF23.
Author Summary
A recent study demonstrated that the inactivating mutations in the FAM20C gene were associated with lethal osteosclerotic bone dysplasia characterized by a generalized hardening of all bones; this observation implied an inhibitory role of FAM20C during bone formation. However, in vitro studies revealed a contradictory finding that FAM20C accelerated the differentiation of cells forming the mineralized tissues. Here we generated Fam20c conditional knockout (cKO) mice, in which the gene was inactivated either in all tissues or specifically in the mineralized tissues. We also generated recombinant FAM20C protein and Fam20c transgenic mice. The cKO mice did not mimic the human skeleton abnormalities of osteosclerotic bone dysplasia, but exhibited rickets (softer bone) along with a significant reduction of serum phosphate level and a remarkable elevation of serum FGF23, a hormone known to promote phosphate wasting. A number of differentiation markers of the bone-forming cells were downregulated in the cKO mice. Recombinant FAM20C promoted the differentiation of mouse preosteoblasts. Introducing the Fam20c transgene did not lead to any abnormalities but rescued the bone defects of the cKO mice. Taken together, we conclude that FAM20C promotes the differentiation of osteoblast lineages and regulates phosphate homeostasis via the mediation of FGF23.
PMCID: PMC3355082  PMID: 22615579
15.  Gene-alcohol interactions identify several novel blood pressure loci including a promising locus near SLC16A9 
Frontiers in Genetics  2013;4:277.
Alcohol consumption is a known risk factor for hypertension, with recent candidate studies implicating gene-alcohol interactions in blood pressure (BP) regulation. We used 6882 (predominantly) Caucasian participants aged 20–80 years from the Framingham SNP Health Association Resource (SHARe) to perform a genome-wide analysis of SNP-alcohol interactions on BP traits. We used a two-step approach in the ABEL suite to examine genetic interactions with three alcohol measures (ounces of alcohol consumed per week, drinks consumed per week, and the number of days drinking alcohol per week) on four BP traits [systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse (PP) pressure]. In the first step, we fit a linear mixed model of each BP trait onto age, sex, BMI, and antihypertensive medication while accounting for the phenotypic correlation among relatives. In the second step, we conducted 1 degree-of-freedom (df) score tests of the SNP main effect, alcohol main effect, and SNP-alcohol interaction using the maximum likelihood estimates (MLE) of the parameters from the first step. We then calculated the joint 2 df score test of the SNP main effect and SNP-alcohol interaction using MixABEL. The effect of SNP rs10826334 (near SLC16A9) on SBP was significantly modulated by both the number of alcoholic drinks and the ounces of alcohol consumed per week (p-values of 1.27E-08 and 3.92E-08, respectively). Each copy of the G-allele decreased SBP by 3.79 mmHg in those consuming 14 drinks per week vs. a 0.461 mmHg decrease in non-drinkers. Index SNPs in 20 other loci exhibited suggestive (p-value ≤ 1E-06) associations with BP traits by the 1 df interaction test or joint 2 df test, including 3 rare variants, one low-frequency variant, and SNPs near/in genes ESRRG, FAM179A, CRIPT-SOCS5, KAT2B, ADCY2, GLI3, ZNF716, SLIT1, PDE3A, KERA-LUM, RNF219-AS1, CLEC3A, FBXO15, and IGSF5. SNP-alcohol interactions may enhance discovery of novel variants with large effects that can be targeted with lifestyle modifications.
PMCID: PMC3860258  PMID: 24376456
blood pressure; hypertension; alcohol; genome-wide; gene-alcohol interactions; gene-lifestyle interactions; interaction; GWAS
16.  Risk Stratification by Self-Measured Home Blood Pressure across Categories of Conventional Blood Pressure: A Participant-Level Meta-Analysis 
PLoS Medicine  2014;11(1):e1001591.
Jan Staessen and colleagues compare the risk of cardiovascular, cardiac, or cerebrovascular events in patients with elevated office blood pressure vs. self-measured home blood pressure.
Please see later in the article for the Editors' Summary
The Global Burden of Diseases Study 2010 reported that hypertension is worldwide the leading risk factor for cardiovascular disease, causing 9.4 million deaths annually. We examined to what extent self-measurement of home blood pressure (HBP) refines risk stratification across increasing categories of conventional blood pressure (CBP).
Methods and Findings
This meta-analysis included 5,008 individuals randomly recruited from five populations (56.6% women; mean age, 57.1 y). All were not treated with antihypertensive drugs. In multivariable analyses, hazard ratios (HRs) associated with 10-mm Hg increases in systolic HBP were computed across CBP categories, using the following systolic/diastolic CBP thresholds (in mm Hg): optimal, <120/<80; normal, 120–129/80–84; high-normal, 130–139/85–89; mild hypertension, 140–159/90–99; and severe hypertension, ≥160/≥100.
Over 8.3 y, 522 participants died, and 414, 225, and 194 had cardiovascular, cardiac, and cerebrovascular events, respectively. In participants with optimal or normal CBP, HRs for a composite cardiovascular end point associated with a 10-mm Hg higher systolic HBP were 1.28 (1.01–1.62) and 1.22 (1.00–1.49), respectively. At high-normal CBP and in mild hypertension, the HRs were 1.24 (1.03–1.49) and 1.20 (1.06–1.37), respectively, for all cardiovascular events and 1.33 (1.07–1.65) and 1.30 (1.09–1.56), respectively, for stroke. In severe hypertension, the HRs were not significant (p≥0.20). Among people with optimal, normal, and high-normal CBP, 67 (5.0%), 187 (18.4%), and 315 (30.3%), respectively, had masked hypertension (HBP≥130 mm Hg systolic or ≥85 mm Hg diastolic). Compared to true optimal CBP, masked hypertension was associated with a 2.3-fold (1.5–3.5) higher cardiovascular risk. A limitation was few data from low- and middle-income countries.
HBP substantially refines risk stratification at CBP levels assumed to carry no or only mildly increased risk, in particular in the presence of masked hypertension. Randomized trials could help determine the best use of CBP vs. HBP in guiding BP management. Our study identified a novel indication for HBP, which, in view of its low cost and the increased availability of electronic communication, might be globally applicable, even in remote areas or in low-resource settings.
Please see later in the article for the Editors' Summary
Editors' Summary
Globally, hypertension (high blood pressure) is the leading risk factor for cardiovascular disease and is responsible for 9.4 million deaths annually from heart attacks, stroke, and other cardiovascular diseases. Hypertension, which rarely has any symptoms, is diagnosed by measuring blood pressure, the force that blood circulating in the body exerts on the inside of large blood vessels. Blood pressure is highest when the heart is pumping out blood (systolic blood pressure) and lowest when the heart is refilling (diastolic blood pressure). European guidelines define optimal blood pressure as a systolic blood pressure of less than 120 millimeters of mercury (mm Hg) and a diastolic blood pressure of less than 80 mm Hg (a blood pressure of less than 120/80 mm Hg). Normal blood pressure, high-normal blood pressure, and mild hypertension are defined as blood pressures in the ranges 120–129/80–84 mm Hg, 130–139/85–89 mm Hg, and 140–159/90–99 mm Hg, respectively. A blood pressure of more than 160 mm Hg systolic or 100 mm Hg diastolic indicates severe hypertension. Many factors affect blood pressure; overweight people and individuals who eat salty or fatty food are at high risk of developing hypertension. Lifestyle changes and/or antihypertensive drugs can be used to control hypertension.
Why Was This Study Done?
The current guidelines for the diagnosis and management of hypertension recommend risk stratification based on conventionally measured blood pressure (CBP, the average of two consecutive measurements made at a clinic). However, self-measured home blood pressure (HBP) more accurately predicts outcomes because multiple HBP readings are taken and because HBP measurement avoids the “white-coat effect”—some individuals have a raised blood pressure in a clinical setting but not at home. Could risk stratification across increasing categories of CBP be refined through the use of self-measured HBP, particularly at CBP levels assumed to be associated with no or only mildly increased risk? Here, the researchers undertake a participant-level meta-analysis (a study that uses statistical approaches to pool results from individual participants in several independent studies) to answer this question.
What Did the Researchers Do and Find?
The researchers included 5,008 individuals recruited from five populations and enrolled in the International Database of Home Blood Pressure in Relation to Cardiovascular Outcome (IDHOCO) in their meta-analysis. CBP readings were available for all the participants, who measured their HBP using an oscillometric device (an electronic device for measuring blood pressure). The researchers used information on fatal and nonfatal cardiovascular, cardiac, and cerebrovascular (stroke) events to calculate the hazard ratios (HRs, indicators of increased risk) associated with a 10-mm Hg increase in systolic HBP across standard CBP categories. In participants with optimal CBP, an increase in systolic HBP of 10-mm Hg increased the risk of any cardiovascular event by nearly 30% (an HR of 1.28). Similar HRs were associated with a 10-mm Hg increase in systolic HBP for all cardiovascular events among people with normal and high-normal CBP and with mild hypertension, but for people with severe hypertension, systolic HBP did not significantly add to the prediction of any end point. Among people with optimal, normal, and high-normal CBP, 5%, 18.4%, and 30.4%, respectively, had a HBP of 130/85 or higher (“masked hypertension,” a higher blood pressure in daily life than in a clinical setting). Finally, compared to individuals with optimal CBP without masked hypertension, individuals with masked hypertension had more than double the risk of cardiovascular disease.
What Do These Findings Mean?
These findings indicate that HBP measurements, particularly in individuals with masked hypertension, refine risk stratification at CBP levels assumed to be associated with no or mildly elevated risk of cardiovascular disease. That is, HBP measurements can improve the prediction of cardiovascular complications or death among individuals with optimal, normal, and high-normal CBP but not among individuals with severe hypertension. Clinical trials are needed to test whether the identification and treatment of masked hypertension leads to a reduction of cardiovascular complications and is cost-effective compared to the current standard of care, which does not include HBP measurements and does not treat people with normal or high-normal CBP. Until then, these findings provide support for including HBP monitoring in primary prevention strategies for cardiovascular disease among individuals at risk for masked hypertension (for example, people with diabetes), and for carrying out HBP monitoring in people with a normal CBP but unexplained signs of hypertensive target organ damage.
Additional Information
Please access these websites via the online version of this summary at
This study is further discussed in a PLOS Medicine Perspective by Mark Caulfield
The US National Heart, Lung, and Blood Institute has patient information about high blood pressure (in English and Spanish) and a guide to lowering high blood pressure that includes personal stories
The American Heart Association provides information on high blood pressure and on cardiovascular diseases (in several languages); it also provides personal stories about dealing with high blood pressure
The UK National Health Service Choices website provides detailed information for patients about hypertension (including a personal story) and about cardiovascular disease
The World Health Organization provides information on cardiovascular disease and controlling blood pressure; its A Global Brief on Hypertension was published on World Health Day 2013
The UK charity Blood Pressure UK provides information about white-coat hypertension and about home blood pressure monitoring
MedlinePlus provides links to further information about high blood pressure, heart disease, and stroke (in English and Spanish)
PMCID: PMC3897370  PMID: 24465187
17.  The Association of a SNP Upstream of INSIG2 with Body Mass Index is Reproduced in Several but Not All Cohorts 
PLoS Genetics  2007;3(4):e61.
A SNP upstream of the INSIG2 gene, rs7566605, was recently found to be associated with obesity as measured by body mass index (BMI) by Herbert and colleagues. The association between increased BMI and homozygosity for the minor allele was first observed in data from a genome-wide association scan of 86,604 SNPs in 923 related individuals from the Framingham Heart Study offspring cohort. The association was reproduced in four additional cohorts, but was not seen in a fifth cohort. To further assess the general reproducibility of this association, we genotyped rs7566605 in nine large cohorts from eight populations across multiple ethnicities (total n = 16,969). We tested this variant for association with BMI in each sample under a recessive model using family-based, population-based, and case-control designs. We observed a significant (p < 0.05) association in five cohorts but saw no association in three other cohorts. There was variability in the strength of association evidence across examination cycles in longitudinal data from unrelated individuals in the Framingham Heart Study Offspring cohort. A combined analysis revealed significant independent validation of this association in both unrelated (p = 0.046) and family-based (p = 0.004) samples. The estimated risk conferred by this allele is small, and could easily be masked by small sample size, population stratification, or other confounders. These validation studies suggest that the original association is less likely to be spurious, but the failure to observe an association in every data set suggests that the effect of SNP rs7566605 on BMI may be heterogeneous across population samples.
Author Summary
Obesity is an epidemic in the United States of America and developing world, portending an epidemic of related diseases such as diabetes and heart disease. While diet and lifestyle contribute to obesity, half of the population variation in body mass index, a common measure of obesity, is determined by inherited factors. Many studies have reported that common sequence variants in genes are associated with an increased risk for obesity, yet most of these are not reproducible in other study cohorts, suggesting that some are false. Recently, Herbert et al. reported a slightly increased risk of obesity for people carrying two copies of the minor allele at a common variant near INSIG2. We present our attempts to further evaluate this potential association with obesity in additional populations. We find evidence of increased risk of obesity for people carrying two copies of the minor allele in five out of nine cohorts tested, using both family- and population-based testing. We indicate possible reasons for the varied results, with the hope of encouraging a combined analysis across study cohorts to more precisely define the effect of this INSIG2 gene variant.
PMCID: PMC1857727  PMID: 17465681
18.  Association of Variable Number of Tandem Repeats in the Coding Region of the FAM46A Gene, FAM46A rs11040 SNP and BAG6 rs3117582 SNP with Susceptibility to Tuberculosis 
PLoS ONE  2014;9(3):e91385.
We analyzed for association between the Family with sequence similarity 46, member A (FAM46A) gene (located on chromosome 6q14.1), BCL2-Associated Athanogene 6 (BAG6) gene (located on chromosome 6p21.3) and tuberculosis in Croatian Caucasian. We genotyped the FAM46A rs11040 SNP, FAM46A VNTR and BAG6 rs3117582 polymorphisms in a case-control study with 257 tuberculosis patients and 493 healthy individuals in a Croatian Caucasian population. We found that genotype FAM46A 3/3 (three VNTR repeats homozygote) was associated with susceptibility to tuberculosis (p<0.0015, Pcorr.<0.029, Odds ratio = 2.42, 95% Confidence Interval = 1.34–4.3). This association suggests that the protein domain encoded by the VNTR might be important for the function of the FAM46A protein, which, in turn, could be relevant in developing tuberculosis. In addition, we found that FAM46A rs11040 SNP:FAM46A VNTR:BAG6 haplotype 132 (G-3-C) is associated with susceptibility to tuberculosis (p<0.012, pcorr.<0.024, Odds ratio 3.45, 95% Confidence Interval = 1.26–9.74). This may suggests that the interaction between the FAM46A and BAG6 proteins may be involved in tuberculosis etiology. We found also that infection of human macrophages with heat-killed M. tuberculosis (H37Rv) led to over-expression of FAM46A (VNTR 3/4) transcript. This is the first study to show associations between the FAM46A gene VNTR polymorphisms, FAM46A rs11040 SNP:FAM46A VNTR:BAG6 haplotypes and any disease.
PMCID: PMC3953334  PMID: 24625963
19.  Admixture-Matched Case-Control Study: A Practical Approach for Genetic Association Studies in Admixed Populations 
Human genetics  2005;118(5):626-639.
Case-control genetic association studies in admixed populations are known to be susceptible to genetic confounding due to population stratification. The transmission/disequilibrium test (TDT) approach can avoid this problem. However, the TDT is expensive and impractical for late- onset diseases. Case-control study designs, in which cases and controls are matched by admixture, can be an appealing and suitable alternative for genetic association studies in admixed populations. In this study, we applied this matching strategy when recruiting our African American participants in the Study of African American, Asthma, Genes and Environments (SAGE). Group admixture in this cohort consists of 83% African ancestry and 17% European ancestry, which was consistent with reports from other studies. By carrying out several complementary analyses, our results show that there is substructure in the cohort, but that the admixture distributions are almost identical in cases and controls, and also in cases only. We performed association tests for asthma-related traits with ancestry, and only found that FEV1, a measure for baseline pulmonary function, was associated with ancestry after adjusting for socio-economic and environmental risk factors (P = 0.01). We did not observe an excess of type I error rate in our association tests for ancestry informative markers (AIMs) and asthma-related phenotypes when ancestry was not adjusted in the analyses. Furthermore, using the association tests between genetic variants in a known asthma candidate gene, β2 adrenergic receptor (β2AR) and ΔFEF25-75, an asthma-related phenotype, as an example, we demonstrated population stratification was not a confounder in our genetic association. Our present work demonstrates that admixture-matched case-control strategies can efficiently control for population stratification confounding in admixed populations.
PMCID: PMC3478103  PMID: 16273390
20.  The Power of the Transmission Disequilibrium Test in the presence of population stratification 
The Transmission Disequilibrium Test (TDT) is a family-based test for association based on the rate of transmission of alleles from heterozygous parents to affected offspring, and has gained popularity as this test preserves the Type I error rate. Population stratification results in a decreased number of heterozygous parents compared to that expected assuming Hardy-Weinberg Equilibrium (Wahlund Effect). We show that population stratification changes the relative proportion of the informative mating types. The decrease in the number of heterozygous parents and the change in the relative proportion of the informative mating types result in significant changes to the sample sizes required to achieve the power desired. We show examples of the changes in sample sizes, and provide an easy method for estimating TDT sample sizes in the presence of population stratification. This method potentially aids in reducing the number of false negative association studies.
PMCID: PMC2921480  PMID: 20442746
Transmission disequilibrium test; population stratification; power
21.  The power of the Transmission Disequilibrium Test in the presence of population stratification 
European Journal of Human Genetics  2010;18(9):1032-1038.
The Transmission Disequilibrium Test (TDT) is a family-based test for association based on the rate of transmission of alleles from heterozygous parents to affected offspring, and has gained popularity as this test preserves the Type I error rate. Population stratification results in a decreased number of heterozygous parents compared to that expected assuming Hardy–Weinberg Equilibrium (Wahlund Effect). We show that population stratification changes the relative proportion of the informative mating types. The decrease in the number of heterozygous parents and the change in the relative proportion of the informative mating types result in significant changes to the sample sizes required to achieve the power desired. We show examples of the changes in sample sizes, and provide an easy method for estimating TDT sample sizes in the presence of population stratification. This method potentially aids in reducing the number of false-negative association studies.
PMCID: PMC2921480  PMID: 20442746
Transmission Disequilibrium Test; population stratification; power
22.  The Future Is Now – Will the Real Disease Gene Please Stand Up? 
Human Heredity  2008;66(2):127-135.
The transmission/disequilibrium test (TDT) [Spielman et al.: Am J Hum Genet 1993;52:506–516] has been postulated as the future of gene mapping for complex diseases, provided one is able to genotype a dense enough map of markers across the genome. Risch and Merikangas [Science 1996;273:1516–1517] suggested a million-marker screen in affected sibpair (ASP) families, demonstrating that the TDT is a more powerful test of linkage than traditional linkage tests based on allele-sharing when there is also association between marker and disease alleles. While the future of genotyping has arrived, successes in family-based association studies have been modest. This is often attributed to excessive false positives in candidate gene studies. This problem is only exacerbated by the increasing numbers of whole genome association (WGA) screens. When applied in ASPs, the TDT statistic, which assumes transmissions to siblings are independent, is not expected to have a constant variance in the presence of variable linkage. This results in generally more extreme statistics, hence will further aggravate the problem of having a large number of positive results to sort through. So an important question is how many positive TDT results will show up on a chromosome containing a disease gene due only to linkage, and will they obfuscate the true disease gene location. To answer this question we combined theory and computer simulations. These studies show that in ASPs the normal version of the TDT statistic has a mean of 0 and a variance of 1 in unlinked regions, but has a variance larger than 1 in linked regions. In contrast, the pedigree disequilibrium test (PDT) statistic adjusts for correlation between siblings due to linkage and maintains a constant variance of 1 at unassociated markers irrespective of linkage. The TDT statistic is generally larger than the PDT statistic across linked regions. This is true for unassociated as well as associated markers. To compare the two tests we ranked both statistics at the disease locus, or an associated marker, among statistics at all other markers. The TDT did better job than PDT placing the score of the associated marker near the top. Though, strictly speaking, the TDT in ASPs should be interpreted as a test of linkage and not a test of association, there is a good chance that if a marker stands out, the marker is associated as well as linked. In conclusion, our results suggest that TDT is an effective screening tool for WGA studies, especially in multiplex families.
PMCID: PMC2861528  PMID: 18382092
Linkage; Linkage disequilibrium; Family-based tests of association; TDT
23.  The Relationships Between FAM5C SNP (rs10920501) Variability and Metabolic Syndrome and Inflammation in Women With Coronary Heart Disease 
Biological research for nursing  2011;15(2):160-166.
The leading cause of death among women is coronary heart disease (CHD), a multifactorial disease with polygenic heritability estimated at 50%. Polymorphisms in the family with sequence similarity 5, member C′ (FAM5C) gene have been associated with myocardial infarction (MI). FAM5C also corresponds directly with the inflammatory biomarker monocyte chemoattractant protein 1 (MCP-1) and metabolic syndrome.
The purpose of this descriptive gene association pilot study was to investigate the variability of FAM5C (rs10920501) in 91 women with CHD. The authors also examined the associations between the variability of FAM5C (rs10920501) and metabolic syndrome, inflammatory markers, and early onset CHD.
No women in this study with the homozygous variant (TT) had an MI. Women with a history of MI and the heterozygous (AT) genotype had a later age of onset of CHD compared to those with the homozygous wild type (AA; F(3, 34) = 5.00, p < .01). These findings suggest a protective effect of the T allele in women with a history of MI. The genotype of FAM5C rs10920501 explained approximately 7% of the variability of age of onset of CHD in women who have had an MI, while holding body mass index (BMI) and smoking history constant. There was no significant relationship between FAM5C (rs10920501) and metabolic syndrome or any inflammatory biomarkers in this sample.
FAM5C remains a gene of interest in a complex disease process.
PMCID: PMC4108984  PMID: 22013132
FAM5C; women; atherosclerosis; metabolic syndrome; inflammation; obesity
24.  Genome-wide association filtering using a highly locus-specific transmission/disequilibrium test 
Human Genetics  2010;128(3):325-344.
Multimarker transmission/disequilibrium tests (TDTs) are powerful association and linkage tests used to perform genome-wide filtering in the search for disease susceptibility loci. In contrast to case/control studies, they have a low rate of false positives for population stratification and admixture. However, the length of a region found in association with a disease is usually very large because of linkage disequilibrium (LD). Here, we define a multimarker proportional TDT (mTDTP) designed to improve locus specificity in complex diseases that has good power compared to the most powerful multimarker TDTs. The test is a simple generalization of a multimarker TDT in which haplotype frequencies are used to weight the effect that each haplotype has on the whole measure. Two concepts underlie the features of the metric: the ‘common disease, common variant’ hypothesis and the decrease in LD with chromosomal distance. Because of this decrease, the frequency of haplotypes in strong LD with common disease variants decreases with increasing distance from the disease susceptibility locus. Thus, our haplotype proportional test has higher locus specificity than common multimarker TDTs that assume a uniform distribution of haplotype probabilities. Because of the common variant hypothesis, risk haplotypes at a given locus are relatively frequent and a metric that weights partial results for each haplotype by its frequency will be as powerful as the most powerful multimarker TDTs. Simulations and real data sets demonstrate that the test has good power compared with the best tests but has remarkably higher locus specificity, so that the association rate decreases at a higher rate with distance from a disease susceptibility or disease protective locus.
PMCID: PMC2921505  PMID: 20603721
25.  Dosage Transmission Disequilibrium Test (dTDT) for Linkage and Association Detection 
PLoS ONE  2013;8(5):e63526.
Both linkage and association studies have been successfully applied to identify disease susceptibility genes with genetic markers such as microsatellites and Single Nucleotide Polymorphisms (SNPs). As one of the traditional family-based studies, the Transmission/Disequilibrium Test (TDT) measures the over-transmission of an allele in a trio from its heterozygous parents to the affected offspring and can be potentially useful to identify genetic determinants for complex disorders. However, there is reduced information when complete trio information is unavailable. In this study, we developed a novel approach to “infer” the transmission of SNPs by combining both the linkage and association data, which uses microsatellite markers from families informative for linkage together with SNP markers from the offspring who are genotyped for both linkage and a Genome-Wide Association Study (GWAS). We generalized the traditional TDT to process these inferred dosage probabilities, which we name as the dosage-TDT (dTDT). For evaluation purpose, we developed a simulation procedure to assess its operating characteristics. We applied the dTDT to the simulated data and documented the power of the dTDT under a number of different realistic scenarios. Finally, we applied our methods to a family study of alcohol dependence (COGA) and performed individual genotyping on complete families for the top signals. One SNP (rs4903712 on chromosome 14) remained significant after correcting for multiple testing Methods developed in this study can be adapted to other platforms and will have widespread applicability in genomic research when case-control GWAS data are collected in families with existing linkage data.
PMCID: PMC3653954  PMID: 23691058

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