Age at menarche (AM) and age at natural menopause (ANM) define the boundaries of the reproductive lifespan in women. Their timing is associated with various diseases, including cancer and cardiovascular disease. Genome-wide association studies have identified several genetic variants associated with either AM or ANM in populations of largely European or Asian descent women. The extent to which these associations generalize to diverse populations remains unknown. Therefore, we sought to replicate previously reported AM and ANM findings and to identify novel AM and ANM variants using the Metabochip (n = 161,098 SNPs) in 4,159 and 1,860 African American women, respectively, in the Women’s Health Initiative (WHI) and Atherosclerosis Risk in Communities (ARIC) studies, as part of the Population Architecture using Genomics and Epidemiology (PAGE) Study. We replicated or generalized one previously identified variant for AM, rs1361108/CENPW, and two variants for ANM, rs897798/BRSK1 and rs769450/APOE, to our African American cohort. Overall, generalization of the majority of previously-identified variants for AM and ANM, including LIN28B and MCM8, was not observed in this African American sample. We identified three novel loci associated with ANM that reached significance after multiple testing correction (LDLR rs189596789, p = 5×10−08; KCNQ1 rs79972789, p = 1.9×10−07; COL4A3BP rs181686584, p = 2.9×10−07). Our most significant AM association was upstream of RSF1, a gene implicated in ovarian and breast cancers (rs11604207, p = 1.6×10−06). While most associations were identified in either AM or ANM, we did identify genes suggestively associated with both: PHACTR1 and ARHGAP42. The lack of generalization coupled with the potentially novel associations identified here emphasize the need for additional genetic discovery efforts for AM and ANM in diverse populations.

Genetic imputation has become standard practice in modern genetic studies. However, several important issues have not been adequately addressed including the utility of study-specific reference, performance in admixed populations, and quality for less common (minor allele frequency [MAF] 0.005–0.05) and rare (MAF < 0.005) variants. These issues only recently became addressable with genome-wide association studies (GWAS) follow-up studies using dense genotyping or sequencing in large samples of non-European individuals. In this work, we constructed a study-specific reference panel of 3,924 haplotypes using African Americans in the Women’s Health Initiative (WHI) genotyped on both the Metabochip and the Affymetrix 6.0 GWAS platform. We used this reference panel to impute into 6,459 WHI SNP Health Association Resource (SHARe) study subjects with only GWAS genotypes. Our analysis confirmed the imputation quality metric Rsq (estimated r2, specific to each SNP) as an effective post-imputation filter. We recommend different Rsq thresholds for different MAF categories such that the average (across SNPs) Rsq is above the desired dosage r2 (squared Pearson correlation between imputed and experimental genotypes).With a desired dosage r2 of 80%, 99.9% (97.5%, 83.6%, 52.0%, 20.5%) of SNPs with MAF > 0.05 (0.03–0.05, 0.01–0.03, 0.005–0.01, and 0.001–0.005) passed the post-imputation filter. The average dosage r2 for these SNPs is 94.7%, 92.1%, 89.0%, 83.1%, and 79.7%, respectively. These results suggest that for African Americans imputation of Metabochip SNPs from GWAS data, including low frequency SNPs with MAF 0.005–0.05, is feasible and worthwhile for power increase in downstream association analysis provided a sizable reference panel is available.

Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype–phenotype associations, 26 represented phenotypes closely related to previously known genotype–phenotype associations, and 33 represented potentially novel genotype–phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits.

Author Summary

In phenome-wide association studies (PheWAS) all potential genetic variants in a dataset are systematically tested for association with all available phenotypes and traits that have been measured in study participants. By investigating the relationship between genetic variation and a diversity of phenotypes, there is the potential for uncovering novel relationships between single nucleotide polymorphisms (SNPs), phenotypes, and networks of interrelated phenotypes. PheWAS also can expose pleiotropy, provide novel mechanistic insights, and foster hypothesis generation. This approach is complementary to genome-wide association studies (GWAS) that test the association between hundreds of thousands, to over a million, single nucleotide polymorphisms and a single phenotype or limited phenotypic domain. The Population Architecture using Genomics and Epidemiology (PAGE) network has measures for a wide array of phenotypes and traits, including prevalent and incident status for clinical conditions and risk factors, as well as clinical parameters and intermediate biomarkers. We performed tests of association between a series of genome-wide association study (GWAS)–identified SNPs and a comprehensive range of phenotypes from the PAGE network in a high-throughput manner. We replicated a number of previously reported associations, validating the PheWAS approach. We also identified novel genotype–phenotype associations possibly representing pleiotropic effects.

Genetic variants in intron 1 of the fat mass– and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI–associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped a 646–kb region, encompassing the large FTO gene and the flanking gene RPGRIP1L by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known FTO intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3×10−6) had not been highlighted in previous studies. While rs56137030was correlated at r2>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor CUX1, which has recently been implicated in the regulation of FTO. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known FTO locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations.

Author Summary

Genetic variants within the fat mass– and obesity-associated (FTO) gene are associated with increased risk of obesity. To better understand which specific genetic variant(s) in this genetic region is associated with obesity risk, we attempt to genotype or impute all known genetic variants in the region and test for association with body mass index as a measurement of obesity in over 20,000 African Americans. We identified 29 potential candidate variants, of which one variant (rs1421085) is a particularly interesting candidate for future functional follow-up studies. Our example shows the powerful approach of studying a large African American population, substantially reducing the number of possible functional variants compared with European descent populations.

Background

Although smoking behavior is known to affect body mass index (BMI), the potential for smoking to influence genetic associations with BMI is largely unexplored.

Methods

As part of the ‘Population Architecture using Genomics and Epidemiology (PAGE)’ Consortium, we investigated interaction between genetic risk factors associated with BMI and smoking for 10 single nucleotide polymorphisms (SNPs) previously identified in genome-wide association studies. We included 6 studies with a total of 56,466 subjects (16,750 African Americans (AA) and 39,716 European Americans (EA)). We assessed effect modification by testing an interaction term for each SNP and smoking (current vs. former/never) in the linear regression and by stratified analyses.

Results

We did not observe strong evidence for interactions and only observed two interactions with p-values <0.1: for rs6548238/TMEM18, the risk allele (C) was associated with BMI only among AA females who were former/never smokers (β = 0.018, p = 0.002), vs. current smokers (β = 0.001, p = 0.95, pinteraction = 0.10). For rs9939609/FTO, the A allele was more strongly associated with BMI among current smoker EA females (β = 0.017, p = 3.5x10-5), vs. former/never smokers (β = 0.006, p = 0.05, pinteraction = 0.08).

Conclusions

These analyses provide limited evidence that smoking status may modify genetic effects of previously identified genetic risk factors for BMI. Larger studies are needed to follow up our results.

Clinical Trial Registration

NCT00000611

Background

Genome wide association studies identified several single nucleotide polymorphisms (SNPs) associated with prevalent coronary heart disease (CHD) but less is known of associations with incident CHD. The association of thirteen published CHD SNPs was examined in five ancestry groups of four large US prospective cohorts.

Methods and Results

The analyses included incident coronary events over 9.1 to 15.7 average follow-up times in up to 26,617 white individuals (6,626 events), 8,018 African Americans (914 events), 1,903 Hispanics (113 events), 3,669 American Indians (595 events) and 885 Asian/Pacific Islanders (66 events). We used Cox proportional hazards models (with additive mode of inheritance) adjusted for age, sex and ancestry (as needed). Nine loci were statistically associated with incident CHD events in whites: 9p21 (rs10757278, p=4.7 × 10−41), 16q23.1 (rs2549513, p=0.0004), 6p24.1 (rs499818, p=0.0002), 2q36.3 (rs2943634, p=6.7 × 10−6), MTHFDIL (rs6922269, p=5.1 × 10−10), APOE (rs429358, p=2.7 × 10−18), ZNF627 (rs4804611, p=5.0 × 10−8), CXCL12 (rs501120, p=1.4 × 10−6) and LPL (rs268, p=2.7 × 10−17). The 9p21 region showed significant between-study heterogeneity, with larger effects in individuals aged 55 years or younger and in women. Inclusion of coronary revascularization procedures among the incident CHD events introduced heterogeneity. The SNPs were not associated with CHD in African Americans and associations varied in other US minorities.

Conclusions

Prospective analyses of white individuals replicated several reported cross-sectional CHD-SNP associations.

Genome-wide association studies (GWAS) have successfully identified numerous genetic loci that are associated with phenotypic traits and diseases. GWAS Integrator is a bioinformatics tool that integrates information on these associations from the National Human Genome Research institute (NHGRI) Catalog, SNAP (SNP Annotation and Proxy Search), and the Human Genome Epidemiology (HuGE) Navigator literature database. This tool includes robust search and data mining functionalities that can be used to quickly identify relevant associations from GWAS, as well as proxy single-nucleotide polymorphisms (SNPs) and potential candidate genes. Query-based University of California Santa Cruz (UCSC) Genome Browser custom tracks are generated dynamically on the basis of users' selected GWAS hits or candidate genes from HuGE Navigator literature database (http://www.hugenavigator.net/HuGENavigator/gWAHitStartPage.do). The GWAS Integrator may help enhance inference on potential genetic associations identified from GWAS studies.

The QT interval (QT) is heritable and its prolongation is a risk factor for ventricular tachyarrhythmias and sudden death. Most genetic studies of QT have examined European ancestral populations; however, the increased genetic diversity in African Americans provides opportunities to narrow association signals and identify population-specific variants. We therefore evaluated 6,670 SNPs spanning eleven previously identified QT loci in 8,644 African American participants from two Population Architecture using Genomics and Epidemiology (PAGE) studies: the Atherosclerosis Risk in Communities study and Women's Health Initiative Clinical Trial. Of the fifteen known independent QT variants at the eleven previously identified loci, six were significantly associated with QT in African American populations (P≤1.20×10−4): ATP1B1, PLN1, KCNQ1, NDRG4, and two NOS1AP independent signals. We also identified three population-specific signals significantly associated with QT in African Americans (P≤1.37×10−5): one at NOS1AP and two at ATP1B1. Linkage disequilibrium (LD) patterns in African Americans assisted in narrowing the region likely to contain the functional variants for several loci. For example, African American LD patterns showed that 0 SNPs were in LD with NOS1AP signal rs12143842, compared with European LD patterns that indicated 87 SNPs, which spanned 114.2 Kb, were in LD with rs12143842. Finally, bioinformatic-based characterization of the nine African American signals pointed to functional candidates located exclusively within non-coding regions, including predicted binding sites for transcription factors such as TBX5, which has been implicated in cardiac structure and conductance. In this detailed evaluation of QT loci, we identified several African Americans SNPs that better define the association with QT and successfully narrowed intervals surrounding established loci. These results demonstrate that the same loci influence variation in QT across multiple populations, that novel signals exist in African Americans, and that the SNPs identified as strong candidates for functional evaluation implicate gene regulatory dysfunction in QT prolongation.

Author Summary

The QT interval (QT) provides a measure of a ventricular action potential, and its prolongation is associated with sudden death and ventricular arrhythmias. Genome-wide association studies performed in European populations have identified common genetic variants that influence QT. However, it is unclear whether these variants are relevant in other populations, including African Americans. The increased genetic diversity in African Americans also provides opportunities to narrow association signals and identify candidates for functional evaluation. We therefore used data from 8,644 African Americans to further characterize previously identified QT loci. Of the fifteen known independent QT variants at the eleven previously identified QT loci, six were associated with QT in African Americans. We also identified three variants that were independent from previously reported signals and narrowed intervals flanking association signals using patterns of linkage disequilibrium. Finally, bioinformatic-based characterization pointed to candidates located outside protein coding regions. Our results underscore the utility of genetic studies in African ancestral populations to identify novel variants and narrow intervals surrounding established loci. These results suggest that known QT loci are important in African Americans and that further characterization of these loci in other populations may provide additional insights into the genetic and molecular mechanisms underlying QT.

Genome-wide association studies have broadened our understanding of the genetic architecture of cancer to include common variants, in addition to the rare variants previously identified by linkage analysis. We review current knowledge on the genetic architecture of four cancers—breast, lung, prostate and colorectal—for which the balance of common and rare alleles identified ranges from fewer common alleles (lung cancer) to more common alleles (prostate cancer). Although most variants are cancer specific, pleiotropy has been observed for several variants, for example, variants at the 8q24 locus and breast, ovarian and prostate cancers or variants in KITLG in relation to hair color and testicular cancer. Although few studies have been adequately powered to investigate heterogeneity among ancestry groups, effect sizes associated with common variants have been reported to be fairly homogenous among ethnic groups. Some associations appear to be ancestry specific, such as HNF1B, which is associated with prostate cancer in European Americans and Latinos but not in African-Americans. Studies of cancer and other complex diseases suggest that a simple dichotomy between rare and common allelic architectures may be too simplistic and that future research is needed to characterize a fuller spectrum of allele frequency (common (>5%), uncommon (1–5%) and rare (<<1%) alleles) and effect size. In addition, a broadening of the concept of genetic architecture to encompass both population architecture, which reflects differences in exposures, genetic factors and population level risk among diverse groups of people, and genomic architecture, which includes structural, epigenomic and somatic variation, is envisioned.

The Metabochip is a custom genotyping array designed for replication and fine mapping of metabolic, cardiovascular, and anthropometric trait loci and includes low frequency variation content identified from the 1000 Genomes Project. It has 196,725 SNPs concentrated in 257 genomic regions. We evaluated the Metabochip in 5,863 African Americans; 89% of all SNPs passed rigorous quality control with a call rate of 99.9%. Two examples illustrate the value of fine mapping with the Metabochip in African-ancestry populations. At CELSR2/PSRC1/SORT1, we found the strongest associated SNP for LDL-C to be rs12740374 (p = 3.5×10−11), a SNP indistinguishable from multiple SNPs in European ancestry samples due to high correlation. Its distinct signal supports functional studies elsewhere suggesting a causal role in LDL-C. At CETP we found rs17231520, with risk allele frequency 0.07 in African Americans, to be associated with HDL-C (p = 7.2×10−36). This variant is very rare in Europeans and not tagged in common GWAS arrays, but was identified as associated with HDL-C in African Americans in a single-gene study. Our results, one narrowing the risk interval and the other revealing an associated variant not found in Europeans, demonstrate the advantages of high-density genotyping of common and rare variation for fine mapping of trait loci in African American samples.

Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.

Author Summary

The metabolic syndrome represents a clustering of metabolic phenotypes (e.g. elevated blood pressure, cholesterol levels, and plasma glucose, as well as abdominal obesity) and is associated with an increased risk of atherosclerosis and type 2 diabetes. Although multiple genes influencing the specific metabolic syndrome components have been reported, few studies have evaluated the genetic underpinnings of the syndrome as a whole. Here, we describe an approach to evaluate multiple clustered traits, which allows us to test whether common genetic variants influence the co-occurrence of one or more metabolic phenotypes. By examining approximately 20,000 European American and 6,200 African American participants from five studies, we show that three regions on chromosomes 12, 19, and 20 are associated with multiple metabolic phenotypes. These genetic variants are highly intriguing candidates that may increase our understanding of the biologic basis of the clustering of metabolic phenotypes and help identify targets for early intervention.

Genetic studies have identified thousands of variants associated with complex traits. However, most association studies are limited to populations of European descent and a single phenotype. The Population Architecture using Genomics and Epidemiology (PAGE) Study was initiated in 2008 by the National Human Genome Research Institute to investigate the epidemiologic architecture of well-replicated genetic variants associated with complex diseases in several large, ethnically diverse population-based studies. Combining DNA samples and hundreds of phenotypes from multiple cohorts, PAGE is well-suited to address generalization of associations and variability of effects in diverse populations; identify genetic and environmental modifiers; evaluate disease subtypes, intermediate phenotypes, and biomarkers; and investigate associations with novel phenotypes. PAGE investigators harmonize phenotypes across studies where possible and perform coordinated cohort-specific analyses and meta-analyses. PAGE researchers are genotyping thousands of genetic variants in up to 121,000 DNA samples from African-American, white, Hispanic/Latino, Asian/Pacific Islander, and American Indian participants. Initial analyses will focus on single nucleotide polymorphisms (SNPs) associated with obesity, lipids, cardiovascular disease, type 2 diabetes, inflammation, various cancers, and related biomarkers. PAGE SNPs are also assessed for pleiotropy using the “phenome-wide association study” approach, testing each SNP for associations with hundreds of phenotypes. PAGE data will be deposited into the National Center for Biotechnology Information's Database of Genotypes and Phenotypes and made available via a custom browser.

Purpose

To assess the use of the genetic test for Factor V Leiden in clinical practice, physician adherence to national and local guidelines, and impacts of test results on patient management.

Methods

Chart review of all patients tested for Factor V Leiden during a 1-year period (2003) in a large nonprofit health care system (group health) (n = 272).

Results

The test for Factor V Leiden was most often used in nonacute outpatient settings by primary care practitioners, in combination with other tests for procoagulant disorders. Testing was performed more broadly than recommended: 61% of tests met American College of Medical Genetics guidelines, 46% of tests met CAP guidelines, and 37% of tests met group health internal guidelines. The most common rationale for testing was to explain a clinical event (58%). Patient management was modified more often in heterozygotes (54%) than in those with normal results (13%) (P < 0.0001).

Conclusions

The uptake of the test for Factor V Leiden has not followed existing recommendations. Genetic risk information was used to influence patient management in the absence of supporting evidence related to health outcomes. These results underscore the importance of further research concerning effective prevention and treatment strategies for patients with genetic risk to help translate genetic risk information into improved health outcomes.

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS–identified variants in diverse population-based studies. We genotyped 49 GWAS–identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (∼20,000), African American (∼9,000), American Indian (∼6,000), Mexican American/Hispanic (∼2,500), Japanese/East Asian (∼690), and Pacific Islander/Native Hawaiian (∼175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits.

Author Summary

Low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels are well known independent risk factors for cardiovascular disease. Lipid-associated genetic variants are being discovered in genome-wide association studies (GWAS) in samples of European descent, but an insufficient amount of data exist in other populations. Therefore, there is a strong need to characterize the effect of these GWAS–identified variants in more diverse cohorts. In this study, we selected over forty genetic loci previously associated with lipid levels and tested for replication in a large European American cohort. We also investigated if the effect of these variants generalizes to non-European descent populations, including African Americans, American Indians, and Mexican Americans/Hispanics. A majority of these GWAS–identified associations replicated in our European American cohort. However, the ability of associations to generalize across other racial/ethnic populations varied greatly, indicating that some of these GWAS–identified variants may not be functional and are more likely to be in linkage disequilibrium with the functional variant(s).

Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, ‘missing’ heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.

Background

The Factor V Leiden (FVL) genetic test is used by many physicians despite its uncertain clinical utility. This study investigated whether self-reported motivations and behaviors concerning FVL genetic testing differed between two groups of primary care physicians defined by frequency of prior FVL test use.

Methods

In January 2007, 112 primary care physicians (60 frequent, 52 infrequent FVL test users) at Group Health, a large health care delivery system, were surveyed. Survey content areas included: primary reasons and motivating factors for ordering FVL; likelihood of ordering FVL for hypothetical patients; potential barriers to genetic testing, and practices and skills regarding FVL test ordering.

Results

Responses between groups agreed concerning most clinical- or patient-related factors. Frequent-FVL physicians were more likely than infrequent-FVL physicians to report ordering FVL for hypothetical patients with mesenteric venous thrombosis (adjusted OR 4.57, 95% CI 1.55, 13.53) or venous thrombosis following hospital discharge (adjusted OR 3.42, 95% CI 1.30, 8.95). Frequent-FVL physicians were also less likely to agree with several potential barriers to genetic testing and more likely to report high confidence in interpreting and explaining FVL test results.

Conclusions

Generally, both groups of physicians reported similar motivating factors for ordering FVL, and reported behaviors were consistent with existing guidelines. More striking differences were observed for measures such as barriers to and confidence in using genetic tests. Though additional research is necessary to evaluate their impact, these results inform several knowledge-to-practice translation issues that are important to the successful integration of genetic testing into primary care.

Objective

Genetic polymorphisms are associated with lipid-lowering response to statins, but generalizeability to disease endpoints is unclear. The association between 82 common single nucleotide polymorphisms (SNPs) in 6 lipid- or statin-related genes (ABCB1, CETP, HMGCR, LDLR, LIPC, NOS3) and incident nonfatal myocardial infarction (MI) and ischemic stroke was analyzed according to current statin use and overall in a population-based case-control study (856 MI, 368 stroke, 2686 controls).

Methods

Common SNPs were chosen from resequencing data using pairwise linkage disequilibrium. Gene-level analyses (testing global association within a gene) and SNP-level analyses (comparing the number of observed versus expected associations across all genes) were performed using logistic regression, setting nominal statistical significance at p<0.05.

Results

No gene-level interactions with statin use on MI or stroke were identified. Across all genes, 2 SNP-statin interactions on MI were observed (1 ABCB1, 1 LIPC) and 5 interactions on stroke (1 CETP, 4 LIPC). The strongest SNP-statin interaction was for synonymous CETP SNP rs5883 on stroke (p = 0.008). Gene-level associations were present for LIPC and MI (p = 0.026), but not other genes or outcomes. SNP-level associations included 3 SNPs with MI (1 LDLR, 2 LIPC) and 2 SNPs with stroke (1 CETP, 1 LDLR). The number of observed SNP associations was no greater than expected by chance.

Conclusions

Several potential novel associations or interactions of SNPs in ABCB1, CETP, LDLR and LIPC with MI and stroke were identified; however, our results should be regarded as hypothesis-generating until corroborated by other studies.

Variations in candidate genes participating in oxidative stress, inflammation and their interactions are potentially associated with diseases of atherosclerotic origin. We investigated independent and joint associations of variations in cholesterol ester transfer protein (CETP), interleukin 8 (IL8), peroxisome proliferator activator receptor alpha (PPARA) and toll-like receptor 4 (TLR4) genes with incident non-fatal myocardial infarction (MI) or ischemic stroke. In a population-based case-control study, cases (848 MI and 368 ischemic stroke) and controls (2682) were recruited from postmenopausal women and hypertensive men/women who were members of Group Health in Western Washington State. Common tag single nucleotide polymorphisms (n=34) representing gene-wide variations were selected from gene sequencing data using pairwise linkage disequilibrium. Haplotypes were inferred using a modified expectation maximization algorithm. Multivariate logistic regression evaluated individual haplotype and SNP-disease associations in log-additive models. Global haplotype tests assessed overall gene-disease associations. Logic regression was used to evaluate gene-gene interactions. False discovery rates and permutation tests were used for multiple testing adjustment in evaluating independent associations and interactions respectively. Overall, gene-wide variations in PPARA and TLR4 genes were associated with MI. The minor allele of the PPARA SNP, rs4253623, was associated with a higher risk of MI (odds ratio: 1.25, 95%CI: 1.08–1.46) while the minor allele of the TLR4 SNP, rs1927911, was associated with a lower risk of MI (odds ratio: 0.88, 95%CI: 0.77–0.99). No within gene or gene-gene interaction was associated with MI or ischemic stroke risk. Potential SNP-disease associations identified in the current study are novel.

Background

From initiation to plaque rupture, immune system components contribute to atherosclerosis. We investigated variation in inflammation-related genes – Interleukin (IL)-1β, IL-6, C-reactive protein (CRP), IL-10, IL-18, and the Tumor Necrosis Factor (TNF) superfamily [Lymphotoxin(LT)-α, TNF-α, LT-β] – with respect to nonfatal incident myocardial infarction (MI) or ischemic stroke risk.

Methods & Results

A population-based case-control study recruited postmenopausal and/or hypertensive Group Health members aged 30 to 79 years. We chose a subset of single nucleotide polymorphisms (SNPs) to describe common gene-wide variation on the basis of linkage disequilibrium. 36 SNPs, describing 38 common haplotypes for 5 genes and a 3-gene cluster, were genotyped among 856 MI cases, 368 stroke cases, and 2,688 controls. Associations of SNPs or PHASE-inferred haplotypes and risk were estimated using logistic regression; significance of gene-level associations was assessed with global Wald tests and permutation tests. Gene-wide IL-18 variation was associated with higher MI risk and an IL-1B haplotype was associated with lower stroke risk. In secondary analyses of SNPs, we observed associations of several IL-1B polymorphisms with risk of MI or stroke. IL-6, CRP, IL-10, and TNF superfamily gene variation was not associated with MI or stroke risk.

Conclusions

Our results support prior reports associating an IL-18 gene variant and MI risk, contribute additional evidence to reports of IL-1B and cardiovascular risk, and fail to confirm risk differences previously observed for CRP, IL-6, and TNF-α promoter variants.

Common polymorphisms in the CRP gene are associated with plasma CRP levels in population-based studies, but associations with age-related events are uncertain. A previous study of CRP haplotypes in older adults was broadened to include longevity and cause-specific mortality (all-cause, non-cardiovascular (nonCV), and cardiovascular (CV)). Common haplotypes were inferred from four tagSNPs in 4512 whites and five tagSNPs in 812 blacks from the Cardiovascular Health Study, a longitudinal cohort of adults over age 65. Exploratory analyses addressed early versus late mortality. CRP haplotypes were not associated with all-cause mortality or longevity overall in either population, but associations with all-cause mortality differed during early and late periods. In blacks, the haplotype tagged by 3872A (rs1205) was associated with increased risk of nonCV mortality, relative to other haplotypes (adjusted hazard ratio for each additional copy: 1.42, 95% CI: 1.07, 1.87). Relative to other haplotypes, this haplotype was associated with decreased risk of early but not decreased risk of late CV mortality in blacks; among whites, a haplotype tagged by 2667C (rs1800947) gave similar but nonsignificant findings. If confirmed, CRP genetic variants may be weakly associated with CV and nonCV mortality in older adults, particularly in self-identified blacks.

The cyclopropane fatty acid synthase gene (cfa) of Clostridium acetobutylicum ATCC 824 was cloned and overexpressed under the control of the clostridial ptb promoter. The function of the cfa gene was confirmed by complementation of an Escherichia coli cfa-deficient strain in terms of fatty acid composition and growth rate under solvent stress. Constructs expressing cfa were introduced into C. acetobutylicum hosts and cultured in rich glucose broth in static flasks without pH control. Overexpression of the cfa gene in the wild type and in a butyrate kinase-deficient strain increased the cyclopropane fatty acid content of early-log-phase cells as well as initial acid and butanol resistance. However, solvent production in the cfa-overexpressing strain was considerably decreased, while acetate and butyrate levels remained high. The findings suggest that overexpression of cfa results in changes in membrane properties that dampen the full induction of solventogenesis. The overexpression of a marR homologous gene preceding the cfa gene in the clostridial genome resulted in reduced cyclopropane fatty acid accumulation.