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1.  Comparison of two methods for analysis of gene–environment interactions in longitudinal family data: the Framingham heart study 
Gene–environment interaction (GEI) analysis can potentially enhance gene discovery for common complex traits. However, genome-wide interaction analysis is computationally intensive. Moreover, analysis of longitudinal data in families is much more challenging due to the two sources of correlations arising from longitudinal measurements and family relationships. GWIS of longitudinal family data can be a computational bottleneck. Therefore, we compared two methods for analysis of longitudinal family data: a methodologically sound but computationally demanding method using the Kronecker model (KRC) and a computationally more forgiving method using the hierarchical linear model (HLM). The KRC model uses a Kronecker product of an unstructured matrix for correlations among repeated measures (longitudinal) and a compound symmetry matrix for correlations within families at a given visit. The HLM uses an autoregressive covariance matrix for correlations among repeated measures and a random intercept for familial correlations. We compared the two methods using the longitudinal Framingham heart study (FHS) SHARe data. Specifically, we evaluated SNP–alcohol (amount of alcohol consumption) interaction effects on high density lipoprotein cholesterol (HDLC). Keeping the prohibitive computational burden of KRC in mind, we limited the analysis to chromosome 16, where preliminary cross-sectional analysis yielded some interesting results. Our first important finding was that the HLM provided very comparable results but was remarkably faster than the KRC, making HLM the method of choice. Our second finding was that longitudinal analysis provided smaller P-values, thus leading to more significant results, than cross-sectional analysis. This was particularly pronounced in identifying GEIs. We conclude that longitudinal analysis of GEIs is more powerful and that the HLM method is an optimal method of choice as compared to the computationally (prohibitively) intensive KRC method.
doi:10.3389/fgene.2014.00009
PMCID: PMC3906599  PMID: 24523728
gene–environment interactions; longitudinal family data; Framingham heart study; interactions in family data; HLM; SNP–alcohol interactions
2.  The role of SNP-loop diuretic interactions in hypertension across ethnic groups in HyperGEN 
Frontiers in Genetics  2013;4:304.
Blood pressure (BP) is significantly influenced by genetic factors; however, less than 3% of the BP variance has been accounted for by variants identified from genome-wide association studies (GWAS) of primarily European-descent cohorts. Other genetic influences, including gene-environment (GxE) interactions, may explain more of the unexplained variance in BP. African Americans (AA) have a higher prevalence and earlier age of onset of hypertension (HTN) as compared with European Americans (EA); responses to anti-hypertensive drugs vary across race groups. To examine potential interactions between the use of loop diuretics and HTN traits, we analyzed systolic (SBP) and diastolic (DBP) blood BP from 1222 AA and 1231 EA participants in the Hypertension Genetic Epidemiology Network (HyperGEN). Population-specific score tests were used to test associations of SBP and DBP, using a panel of genotyped and imputed single nucleotide polymorphisms (SNPs) for AA (2.9 million SNPs) and EA (2.3 million SNPs). Several promising loci were identified through gene-loop diuretic interactions, although no SNP reached genome-wide significance after adjustment for genomic inflation. In AA, SNPs in or near the genes NUDT12, CHL1, GRIA1, CACNB2, and PYHIN1 were identified for SBP, and SNPs near ID3 were identified for DBP. For EA, promising SNPs for SBP were identified in ESR1 and for DBP in SPATS2L and EYA2. Among these SNPs, none were common across phenotypes or population groups. Biologic plausibility exists for many of the identified genes, suggesting that these are candidate genes for regulation of BP and/or anti-hypertensive drug response. The lack of genome-wide significance is understandable in this small study employing gene-drug interactions. These findings provide a set of prioritized SNPs/candidate genes for future studies in HTN. Studies in more diversified population samples may help identify previously missed variants.
doi:10.3389/fgene.2013.00304
PMCID: PMC3872290  PMID: 24400021
blood pressure; hypertension; loop diuretic; gene-drug interaction; genome-wide association; african americans; european americans
3.  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.
doi:10.3389/fgene.2013.00277
PMCID: PMC3860258  PMID: 24376456
blood pressure; hypertension; alcohol; genome-wide; gene-alcohol interactions; gene-lifestyle interactions; interaction; GWAS
4.  Genome-wide Linkage and Positional Association Study of Blood Pressure Response to Dietary Sodium Intervention 
American Journal of Epidemiology  2012;176(Suppl 7):S81-S90.
The authors conducted a genome-wide linkage scan and positional association analysis to identify the genetic determinants of salt sensitivity of blood pressure (BP) in a large family-based, dietary-feeding study. The dietary intervention was conducted among 1,906 participants in rural China (2003–2005). A 7-day low-sodium intervention was followed by a 7-day high-sodium intervention. Salt sensitivity was defined as BP responses to low- and high-sodium interventions. Signals of the logarithm of the odds to the base 10 (LOD ≥ 3) were detected at 33–42 centimorgans of chromosome 2 (2p24.3-2p24.1), with a maximum LOD score of 3.33 for diastolic blood pressure responses to high-sodium intervention. LOD scores were 2.35–2.91 for mean arterial pressure (MAP) and 0.80–1.49 for systolic blood pressure responses in this region, respectively. Correcting for multiple tests, single nucleotide polymorphism (SNP) rs11674786 (2.7 kilobases upstream of the family with sequence similarity 84, member A, gene (FAM84A)) in the linkage region was significantly associated with diastolic blood pressure (P = 0.0007) and MAP responses (P = 0.0007), and SNP rs16983422 (2.8 kilobases upstream of the visinin-like 1 gene (VSNL1)) was marginally associated with diastolic blood pressure (P = 0.005) and MAP responses (P = 0.005). An additive interaction between SNPs rs11674786 and rs16983422 was observed, with P = 7.00 × 10−5 and P = 7.23 × 10−5 for diastolic blood pressure and MAP responses, respectively. The authors concluded that genetic region 2p24.3-2p24.1 might harbor functional variants for the salt sensitivity of BP.
doi:10.1093/aje/kws290
PMCID: PMC3530365  PMID: 22865701
allelic association; blood pressure; genetic linkage; salt sensitivity
5.  Genome-wide Linkage and Positional Candidate Gene Study of Blood Pressure Response to Dietary Potassium Intervention: The GenSalt Study 
Background
Genetic determinants of BP response to potassium, or potassium sensitivity, are largely unknown. We conducted a genome-wide linkage scan and positional candidate gene analysis to identify genetic determinants of potassium sensitivity.
Methods and Results
1,906 Han Chinese participants took part in a 7-day high-sodium followed by a 7-day high-sodium plus potassium dietary intervention. BP measurements were obtained at baseline and following each intervention using a random-zero sphygmomanometer. Significant linkage signals (LOD>3) for BP responses to potassium were detected at chromosomal regions 3q24-q26.1, 3q28, and 11q22.3-q24.3. Maximum multipoint LOD scores of 3.09 at 3q25.2 and 3.41 at 11q23.3 were observed for absolute DBP and MAP responses, respectively. Linkage peaks of 3.56 at 3q25.1 and 3.01 at 11q23.3 for percent DBP response and 3.22 at 3q25.2, 3.01 at 3q28, and 4.48 at 11q23.3 for percent MAP response were also identified. AGTR1 SNP rs16860760 in the 3q24-q26.1 region was significantly associated with absolute and percent systolic (SBP) responses to potassium (p-values=0.0008 and 0.0006, respectively). Absolute SBP responses (95% CI) for genotypes C/C, C/T, and T/T were: −3.71 (−4.02, −3.40), −2.62 (−3.38, −1.85), and 1.03 (−3.73, 5.79) mmHg, respectively; and percent responses (95% CI) were: −3.07 (−3.33, −2.80), −2.07 (−2.74, −1.41), and 0.90 (−3.20, 4.99), respectively. Similar trends were observed for DBP and MAP responses.
Conclusions
Genetic regions on chromosomes 3 and 11 may harbor important susceptibility loci for potassium sensitivity. Furthermore, the AGTR1 gene was a significant predictor of BP responses to potassium intake.
Clinical Trial Registration Information
http://clinicaltrials.gov; Identifier: NCT00721721
doi:10.1161/CIRCGENETICS.110.940635
PMCID: PMC3102761  PMID: 20861505
blood pressure; potassium; genetics
6.  Genome-wide Linkage Screen for Stature and Body-mass Index in 3.032 Families - Evidence for Sex- and Population-specific Genetic Effects 
Stature (adult body height), and body mass index (BMI) have a strong genetic component explaining observed variation in human populations, however, identifying those genetic components has been extremely challenging. It seems obvious that sample size is a critical determinant for successful identification of quantitative trait loci (QTL) that underlie the genetic architecture of these polygenic traits. The inherent shared environment and known genetic relationships in family studies provide clear advantages for gene mapping over studies utilizing unrelated individuals. To these ends, we combined the genotype and phenotype data from four previously performed family-based genome-wide screens resulting in a sample of 9.371 individuals from 3.032 African-American and European-American families and performed variance-components linkage analyses for stature and BMI. To our knowledge, this study represents the single largest family-based genome-wide linkage scan published for stature and BMI to date. This large study sample allowed us to pursue population-and sex-specific analyses as well. For stature we found evidence for linkage in previously reported loci on 11q23, 12q12, 15q25 and 18q23 as well as 15q26 and 19q13 which have not been linked to stature previously. For BMI we found evidence for two loci: one on 7q35 and another on 11q22 both of which have been previously linked to BMI in multiple populations. Our results show both the benefit of 1) combining data to maximize the sample size and 2) minimizing heterogeneity by analyzing subgroups where within-group variation can be reduced and suggest that the latter may be a more successful approach in genetic mapping.
doi:10.1038/ejhg.2008.152
PMCID: PMC2628452  PMID: 18781184
Body Height; Body Mass Index; Linkage mapping; Quantitative Trait Loci
7.  Genome-wide linkage screen for stature and body mass index in 3.032 families: evidence for sex- and population-specific genetic effects 
Stature (adult body height) and body mass index (BMI) have a strong genetic component explaining observed variation in human populations; however, identifying those genetic components has been extremely challenging. It seems obvious that sample size is a critical determinant for successful identification of quantitative trait loci (QTL) that underlie the genetic architecture of these polygenic traits. The inherent shared environment and known genetic relationships in family studies provide clear advantages for gene mapping over studies utilizing unrelated individuals. To these ends, we combined the genotype and phenotype data from four previously performed family-based genome-wide screens resulting in a sample of 9.371 individuals from 3.032 African-American and European-American families and performed variance-components linkage analyses for stature and BMI. To our knowledge, this study represents the single largest family-based genome-wide linkage scan published for stature and BMI to date. This large study sample allowed us to pursue population- and sex-specific analyses as well. For stature, we found evidence for linkage in previously reported loci on 11q23, 12q12, 15q25 and 18q23, as well as 15q26 and 19q13, which have not been linked to stature previously. For BMI, we found evidence for two loci: one on 7q35 and another on 11q22, both of which have been previously linked to BMI in multiple populations. Our results show both the benefit of (1) combining data to maximize the sample size and (2) minimizing heterogeneity by analyzing subgroups where within-group variation can be reduced and suggest that the latter may be a more successful approach in genetic mapping.
doi:10.1038/ejhg.2008.152
PMCID: PMC2628452  PMID: 18781184
body height; body mass index; linkage mapping; quantitative trait loci
8.  Replication of the Wellcome Trust genome-wide association study of essential hypertension 
Essential hypertension is a principal cardiovascular risk factor whose origin remains unknown. Classical genetic studies have shown that blood pressure is at least partially heritable, opening a window to understanding the pathophysiology of essential hypertension in the human using modern genetic tools. The Welcome Trust Case Control Consortium has recently published the results of screening the genomes of 2,000 essential hypertension cases and 3,000 controls using 500,000 genome-wide single nucleotide polymorphisms. None of the variants proved to be genome-wide significant after correction for multiple tests but the most significantly associated SNPs (P<10-5) constitute a priority list that warrant follow-up in other studies. We describe here replication studies of the top 6 SNPs in subjects from the US National Heart, Lung, and Blood Institute funded Family Blood Pressure Program comprising 11,433 individuals recruited by hypertensive families. The results suggest that only one of the 6 SNPs might be associated with essential hypertension in Americans of European origin. This SNP shows a significant but opposite effect in Americans of Hispanic origin and no association in African-Americans. The significance of the opposing effect estimates is unclear. No replication could be shown for hypertension status, but there are differences in study design. This attempted replication highlights that essential hypertension studies will require more comprehensive and larger genetic screens.
doi:10.1038/ejhg.2008.102
PMCID: PMC2585612  PMID: 18523456
hypertension; blood pressure; genetics; genome-wide association study; replication

Results 1-8 (8)