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Genotype-phenotype association studies often combine phenotype data from multiple studies to increase statistical power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data-set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data-sharing mechanisms. This system was developed for the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other -omics data for more than 80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants (recruited in 1948-2012) from up to 17 studies per phenotype. Here we discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include 1) the software code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify, or extend these harmonizations to additional studies, and 2) the results of labeling thousands of phenotype variables with controlled vocabulary terms.

Human induced pluripotent stem cell (hiPSC) lines have previously been generated through the NHLBI sponsored NextGen program at nine individual study sites. Here, we examined the structural integrity of 506 hiPSC lines as determined by copy number variations (CNVs). We observed that 149 hiPSC lines acquired 258 CNVs relative to donor DNA. We identified six recurrent regions of CNVs on chromosomes 1, 2, 3, 16 and 20 that overlapped with cancer associated genes. Furthermore, the genes mapping to regions of acquired CNVs show an enrichment in cancer related biological processes (IL6 production) and signaling cascades (JNK cascade & NFκB cascade). The genomic region of instability on chr20 (chr20q11.2) includes transcriptomic signatures for cancer associated genes such as ID1, BCL2L1, TPX2, PDRG1 and HCK. Of these HCK shows statistically significant differential expression between carrier and non-carrier hiPSC lines. Overall, while a low level of genomic instability was observed in the NextGen generated hiPSC lines, the observation of structural instability in regions with known cancer associated genes substantiates the importance of systematic evaluation of genetic variations in hiPSCs before using them as disease/research models.

ObjectiveWe sought to identify rare variants influencing brain imaging phenotypes in the Framingham Heart Study by performing whole genome sequence association analyses within the Trans-Omics for Precision Medicine Program.MethodsWe performed association analyses of cerebral and hippocampal volumes and white matter hyperintensity (WMH) in up to 2,180 individuals by testing the association of rank-normalized residuals from mixed-effect linear regression models adjusted for sex, age, and total intracranial volume with individual variants while accounting for familial relatedness. We conducted gene-based tests for rare variants using (1) a sliding-window approach, (2) a selection of functional exonic variants, or (3) all variants.ResultsWe detected new loci in 1p21 for cerebral volume (minor allele frequency [MAF] 0.005, p = 10-8) and in 16q23 for hippocampal volume (MAF 0.05, p = 2.7 × 10-8). Previously identified associations in 12q24 for hippocampal volume (rs7294919, p = 4.4 × 10-4) and in 17q25 for WMH (rs7214628, p = 2.0 × 10-3) were confirmed. Gene-based tests detected associations (p ≤ 2.3 × 10-6) in new loci for cerebral (5q13, 8p12, 9q31, 13q12-q13, 15q24, 17q12, 19q13) and hippocampal volumes (2p12) and WMH (3q13, 4p15) including Alzheimer disease- (UNC5D) and Parkinson disease-associated genes (GBA). Pathway analyses evidenced enrichment of associated genes in immunity, inflammation, and Alzheimer disease and Parkinson disease pathways.ConclusionsWhole genome sequence-wide search reveals intriguing new loci associated with brain measures. Replication of novel loci is needed to confirm these findings.

The exploding volume of whole-genome sequence (WGS) and multi-omics data requires new approaches for analysis. As one solution, we have created a cloud-based Analysis Commons, which brings together genotype and phenotype data from multiple studies in a setting that is accessible by multiple investigators. This framework addresses many of the challenges of multi-center WGS analyses, including data sharing mechanisms, phenotype harmonization, integrated multi-omics analyses, annotation, and computational flexibility. In this setting, the computational pipeline facilitates a sequence-to-discovery analysis workflow illustrated here by an analysis of plasma fibrinogen levels in 3996 individuals from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) WGS program. The Analysis Commons represents a novel model for transforming WGS resources from a massive quantity of phenotypic and genomic data into knowledge of the determinants of health and disease risk in diverse human populations.

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.

Abstract The Framingham Heart Study, founded in 1948 to examine the epidemiology of cardiovascular disease in a small town outside of Boston, has become the worldwide standard for cardiovascular epidemiology. It is among the longest running, most comprehensively characterized multi-generational studies in the world. Such seminal findings as the effects of smoking and high cholesterol on heart disease came from the Framingham Heart Study. At the time of publication these were novel cardiovascular disease (CVD) risk factors, now they are the basis of treatment and prevention in the US. Is the Framingham study now on it's way to becoming the gold standard for genetic epidemiology of CVD? Will the novel genetic findings of today become the health care standards of tomorrow? The accompanying articles summarizing the results of genome-wide association studies (GWAS) give the reader a first glimpse into the possibilities.

Abstract Background Previously, we reported significant linkage of body mass index (BMI) to chromosomes 6 and 11 across six examinations, covering 28 years, of the Framingham Heart Study. These results were on all individuals available at each exam, thus the sample size varied from exam to exam. To remove any effect of sample size variation we have now constructed six subsets; for each exam individuals were only included if they were measured at every exam, i.e. for each exam, included individuals comprise the intersection of the original six exams. This strategy preferentially removed older individuals who died before reaching the sixth exam, thus the intersection datasets are smaller (n = 1114) and significantly younger than the full datasets. We performed variance components linkage analysis on these intersection datasets and on their sex-specific subsets. Results Results from the sex-specific genome scans revealed 11 regions in which a sex-specific maximum lodscore was at least 2.0 for at least one dataset. Randomization tests indicated that all 11 regions had significant (p < 0.05) differences in sex-specific maximum lodscores for at least three datasets. The strongest sex-specific linkage was for men on chromosome 16 with maximum lodscores 2.70, 3.00, 3.42, 3.61, 2.56 and 1.93 for datasets 1–6 respectively. Results from the full genome scans revealed that linked regions on chromosomes 6 and 11 remained significantly and consistently linked in the intersection datasets. Surprisingly, the maximum lodscore on chromosome 10 for dataset 1 increased from 0.97 in the older original dataset to 4.23 in the younger smaller intersection dataset. This difference in maximum lodscores was highly significant (p < 0.0001), implying that the effect of this chromosome may vary with age. Age effects may also exist for the linked regions on chromosomes 6 and 11. Conclusion Sex specific effects of chromosomal regions on BMI are common in the Framingham study. Some evidence also exists for age-specific effects of chromosomal regions.

Chronic kidney disease (CKD) can be a consequence of diabetes, hypertension, immunologic disorders, and other exposures, as well as genetic factors that are still largely unknown. Glomerular filtration rate (GFR), which is widely used to measure kidney function, has a heritability ranging from 25% to 75%, but only 1.5% of this heritability is explained by genetic loci that have been identified to date. In this study we tested for associations between GFR and 234 SNPs in 26 genes from pathways of blood pressure regulation in 3,025 rural Chinese participants of the “Genetic Epidemiology Network of Salt Sensitivity” (GenSalt) study. We estimated GFR (eGFR) using baseline serum creatinine measurements obtained prior to dietary intervention. We identified significant associations between eGFR and 12 SNPs in 6 genes (ACE, ADD1, AGT, GRK4, HSD11B1, and SCNN1G). The cumulative effect of the protective alleles was an increase in mean eGFR of 4 mL/min per 1.73 m2, while the cumulative effect of the risk alleles was a decrease in mean eGFR of 3 mL/min per 1.73 m2. In addition, we identified a significant interaction between SNPs in CYP11B1 and ADRB2. We have identified common variants in genes from pathways that regulate blood pressure and influence kidney function as measured by eGFR, providing new insights into the genetic determinants of kidney function. Complex genetic effects on kidney function likely involve interactions among genes as we observed for CYP11B1 and ADRB2. [ABSTRACT FROM AUTHOR]

BackgroundBlood pressure (BP) homeostasis involves complex interactions among genetic and nongenetic factors, providing major challenges to dissection of the genetic components that influence BP and hypertension. In this study, we examine the effects of interaction of genetic variants with physical activity on BP in a relatively genetically homogenous cohort of rural Chinese villagers.MethodsGeneralized estimating equations analysis was used to test for associations of systolic blood pressure (SBP) and diastolic blood pressure (DBP) with variants in 24 genes in BP pathways (196 single-nucleotide polymorphisms (SNPs)) among 3,142 Chinese participants divided according to physical activity (active vs. inactive groups).ResultsIn the physically active group, two SNPs in NR3C2 were significantly associated with lower SBP, and a SNP in SCNN1B was significantly associated with lower SBP and DBP. In the physically inactive group, a SNP in APLNR was associated with lower SBP, a SNP in GNB3 (guanine nucleotide binding protein, β polypeptide 3) was associated with higher SBP and DBP, and a SNP in BDKRB2 (bradykinin receptor B2) was associated with lower DBP. Cumulative effects in carriers of minor alleles of these SNPs showed reductions of SBP and DBP as large as 8 and 5 mm Hg, respectively, in the active individuals compared to inactive individuals carrying the same number of minor alleles.ConclusionsWe found that physical activity modifies the effects of genetic variants on BP. However, our results also show that active individuals with specific genotypes always have lower BP than inactive individuals with the same genotypes, demonstrating the overall beneficial effects of physical activity on BP.American Journal of Hypertension (2011). doi:10.1038/ajh.2011.97 [ABSTRACT FROM AUTHOR]

BackgroundA preliminary genome-wide linkage analysis of blood pressure in the Family Blood Pressure Program (FBPP) was reported previously. We harnessed the power and ethnic diversity of the final pooled FBPP dataset to identify novel loci for blood pressure thereby enhancing localization of genes containing less common variants with large effects on blood pressure levels and hypertension.MethodsWe performed one overall and 4 race-specific meta-analyses of genome-wide blood pressure linkage scans using data on 4,226 African-American, 2,154 Asian, 4,229 Caucasian, and 2,435 Mexican-American participants (total N = 13,044). Variance components models were fit to measured (raw) blood pressure levels and two types of antihypertensive medication adjusted blood pressure phenotypes within each of 10 subgroups defined by race and network. A modified Fisher's method was used to combine the P values for each linkage marker across the 10 subgroups.ResultsFive quantitative trait loci (QTLs) were detected on chromosomes 6p22.3, 8q23.1, 20q13.12, 21q21.1, and 21q21.3 based on significant linkage evidence (defined by logarithm of odds (lod) score ≥3) in at least one meta-analysis and lod scores ≥1 in at least 2 subgroups defined by network and race. The chromosome 8q23.1 locus was supported by Asian-, Caucasian-, and Mexican-American-specific meta-analyses.ConclusionsThe new QTLs reported justify new candidate gene studies. They may help support results from genome-wide association studies (GWAS) that fall in these QTL regions but fail to achieve the genome-wide significance.American Journal of Hypertension (2011). doi:10.1038/ajh.2010.238 [ABSTRACT FROM AUTHOR]

The article presents information on the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) study. The study shows that increase in potassium intake reduces blood pressure (BP) among hypertensive and normotensive people. According to the author genetic variant AGTR1 gene identified with BP responses to potassium intake.

Background: The etiology of cardiovascular disease (CVD) is multifactorial. Efforts to identify genes influencing CVD risk have met with limited success to date, likely because of the small effect sizes of common CVD risk alleles and the presence of gene by gene and gene by environment interactions.Methods: The HAPI Heart Study was initiated in 2002 to measure the cardiovascular response to 4 short-term interventions affecting cardiovascular risk factors and to identify the genetic and environmental determinants of these responses. The measurements included blood pressure responses to the cold pressor stress test and to a high salt diet, triglyceride excursion in response to a high-fat challenge, and response in platelet aggregation to aspirin therapy.Results: The interventions were carried out in 868 relatively healthy Amish adults from large families. The heritabilities of selected response traits for each intervention ranged from 8% to 38%, suggesting that some of the variation associated with response to each intervention can be attributed to the additive effects of genes.Conclusions: Identifying these response genes may identify new mechanisms influencing CVD and may lead to individualized preventive strategies and improved early detection of high-risk individuals. [ABSTRACT FROM AUTHOR]

Atherosclerosis accounts for 75% of all deaths from cardiovascular disease and includes coronary heart disease (CHD), stroke, and other diseases of the arteries. More than half of all CHD is attributable to abnormalities in levels and metabolism of lipids. To locate genes that affect total cholesterol, high density lipoprotein cholesterol (HDL-C), and triglycerides, genome-wide linkage scans for quantitative trait loci were performed using variance components methods as implemented in SOLAR on a large diverse sample recruited as part of the Family Blood Pressure Program. Phenotype and genetic marker data were available for 9,299 subjects in 2,953 families for total cholesterol, 8,668 subjects in 2,736 families for HDL, and 7,760 subjects in 2,499 families for triglycerides. Mean lipid levels were adjusted for the effects of sex, age, age2, age-by-sex interaction, body mass index, smoking status, and field center. HDL-C and triglycerides were further adjusted for average total alcoholic drinks per week and estrogen use. Significant linkage was found for total cholesterol on chromosome 2 (LOD = 3.1 at 43 cM) in Hispanics and for HDL-C on chromosome 3 (LOD = 3.0 at 182 cM) and 12 (LOD = 3.5 at 124 cM) in Asians. In addition, there were 13 regions that showed suggestive linkage (LOD ≥ 2.0); 7 for total cholesterol, 4 for HDL, and 2 for triglycerides. The identification of these loci affecting lipid phenotypes and the apparent congruence with previous linkage results provides increased support that these regions contain genes influencing lipid levels. [ABSTRACT FROM AUTHOR]

Background: Previously, we reported significant linkage of body mass index (BMI) to chromosomes 6 and 11 across six examinations, covering 28 years, of the Framingham Heart Study. These results were on all individuals available at each exam, thus the sample size varied from exam to exam. To remove any effect of sample size variation we have now constructed six subsets; for each exam individuals were only included if they were measured at every exam, i.e. for each exam, included individuals comprise the intersection of the original six exams. This strategy preferentially removed older individuals who died before reaching the sixth exam, thus the intersection datasets are smaller (n = 1114) and significantly younger than the full datasets. We performed variance components linkage analysis on these intersection datasets and on their sex-specific subsets. Results: Results from the sex-specific genome scans revealed 11 regions in which a sex-specific maximum lodscore was at least 2.0 for at least one dataset. Randomization tests indicated that all 11 regions had significant (p < 0.05) differences in sex-specific maximum lodscores for at least three datasets. The strongest sex-specific linkage was for men on chromosome 16 with maximum lodscores 2.70, 3.00, 3.42, 3.61, 2.56 and 1.93 for datasets 1-6 respectively. Results from the full genome scans revealed that linked regions on chromosomes 6 and 11 remained significantly and consistently linked in the intersection datasets. Surprisingly, the maximum lodscore on chromosome 10 for dataset 1 increased from 0.97 in the older original dataset to 4.23 in the younger smaller intersection dataset. This difference in maximum lodscores was highly significant (p < 0.0001), implying that the effect of this chromosome may vary with age. Age effects may also exist for the linked regions on chromosomes 6 and 11. Conclusion: Sex specific effects of chromosomal regions on BMI are common in the Framingham study. Some evidence also exists for age-specific effects of chromosomal regions. [ABSTRACT FROM AUTHOR]

Adult body mass and changes in mass during an individual's life are important indicators of general health and reproductive fitness. Therefore, characterization of the factors that influence normal variation in body mass has important implications for colony management and husbandry. The main objective of this study was to quantify the genetic contribution to adult body mass and its maintenance in baboons. Intra-individual mean and variance in body mass were calculated from multiple weight measures available for each of 1,614 animals at least 10 years of age. Heritabilities were estimated using maximum likelihood methods. Mean adult body mass had a significant heritability (50%) as did variance in adult body mass (12%). The sexes differed in several respects: on average females were smaller than males and had greater variability in adult body mass; mean and variance in body mass increased with age in females only; and number of offspring showed a significant positive relationship with body mass in females only. There were significant differences between subspecies in body mass as well as ability to maintain body mass. These results indicate that there is a significant genetic influence on body mass and its maintenance, and suggest that different factors influence changes in body mass with age as well as body mass maintenance in male and female baboons. Am. J. Primatol. 42:281–288, 1997. © 1997 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

Background: Elevated levels of low-density lipoprotein cholesterol (LDL-C) are a major risk factor for cardiovascular disease via its contribution to the development and progression of atherosclerotic lesions. Although the genetic basis of LDL-C has been studied extensively, currently known genetic variants account for only ≈20% of the variation in LDL-C levels.Methods: Through an array-based association analysis in 1102 Amish subjects, we identified a variant strongly associated with LDL-C levels. Using a combination of genetic analyses, zebrafish models, and in vitro experiments, we sought to identify the causal gene driving this association.Results: We identified a founder haplotype associated with a 15 mg/dL increase in LDL-C on chromosome 5. After recombination mapping, the associated region contained 8 candidate genes. Using a zebrafish model to evaluate the relevance of these genes to cholesterol metabolism, we found that expression of the transcribed pseudogene, APOOP1, increased LDL-C and vascular plaque formation.Conclusions: Based on these data, we propose that APOOP1 regulates levels of LDL-C in humans, thus identifying a novel mechanism of lipid homeostasis. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To detect novel loci with age-dependent effects on fasting (≥8 h) levels of total cholesterol, high-density lipoprotein, low-density lipoprotein, and triglycerides using 3600 African Americans, 1283 Asians, 3218 European Americans, and 2026 Mexican Americans from the Family Blood Pressure Program (FBPP). Methods: Within each subgroup (defined by network, race, and sex), we employed stepwise linear regression (retention p ≤ 0.05) to adjust lipid levels for age, age-squared, age-cubed, body-mass-index, current smoking status, current drinking status, field center, estrogen therapy (females only), as well as antidiabetic, antihypertensive, and antilipidemic medication use. For each trait, we pooled the standardized male and female residuals within each network and race and fit a generalized variance components model that incorporated gene–age interactions. We conducted FBPP-wide and race-specific meta-analyses by combining the p-values of each linkage marker across subgroups using a modified Fisher's method. Results: We identified seven novel loci with age-dependent effects; four total cholesterol loci from the meta-analysis of Mexican Americans (on chromosomes 2q24.1, 4q21.21, 8q22.2, and 12p11.23) and three high-density lipoprotein loci from the meta-analysis of all FBPP subgroups (on chromosomes 1p12, 14q11.2, and 21q21.1). These loci lacked significant genome-wide linkage or association evidence in the literature and had logarithm of odds (LOD) score ≥ 3 in the meta-analysis with LOD ≥ 1 in at least two network and race subgroups (exclusively of non-European descent). Conclusion: Incorporating gene–age interactions into the analysis of lipids using multi-ethnic cohorts can enhance gene discovery. These interaction loci can guide the selection of families for sequencing studies of lipid-associated variants. [Copyright &y& Elsevier]

The withdrawal of cerivastatin involved an uncommon but serious adverse reaction, rhabdomyolysis. The bimodal response, rhabdomyolysis in a small proportion of users, points to genetic factors as a potential cause. We conducted a case-control study to evaluate genetic markers for cerivastatin-associated rhabdomyolysis.This study had two components: a candidate gene study to evaluate variants in CYP2C8, UGT1A1, UGT1A3, and SLCO1B1; and a genome-wide association study to identify risk factors in other regions of the genome. A total of 185 rhabdomyolysis cases were frequency matched to statin-using controls from the Cardiovascular Health Study (n=374) and the Heart and Vascular Health Study (n=358). Validation relied on functional studies.Permutation test results suggested an association between cerivastatin-associated rhabdomyolysis and variants in SLCO1B1 (P=0.002), but not variants in CYP2C8 (P=0.073) or UGTs (P=0.523). An additional copy of the minor allele of SLCO1B1 rs4149056 (p.Val174Ala) was associated with the risk of rhabdomyolysis (odds ratio: 1.89; 95% confidence interval: 1.40-2.56). In transfected cells, this variant reduced cerivastatin transport by 40% compared with the reference transporter (P<0.001). The genome-wide association study identified an intronic variant (rs2819742) in the ryanodine receptor 2 gene (RYR2) as significant (P=1.74E-07). An additional copy of the minor allele of the RYR2 variant was associated with a reduced risk of rhabdomyolysis (odds ratio: 0.48; 95% confidence interval: 0.36-0.63).We identified modest genetic risk factors for an extreme response to cerivastatin. Disabling genetic variants in the candidate genes were not responsible for the bimodal response to cerivastatin. [ABSTRACT FROM AUTHOR]