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Background: Fibrinogen plays an essential role in blood coagulation and inflammation. Circulating fibrinogen levels may be determined based on interindividual differences in DNA methylation at cytosine-phosphate-guanine (CpG) sites and vice versa. Objectives: To perform an EWAS to examine an association between blood DNA methylation levels and circulating fibrinogen levels to better understand its biological and pathophysiological actions. Methods: We performed an epigenome-wide association study of circulating fibrinogen levels in 18 037 White, Black, American Indian, and Hispanic participants, representing 14 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. Circulating leukocyte DNA methylation was measured using the Illumina 450K array in 12 904 participants and using the EPIC array in 5133 participants. In each study, an epigenome-wide association study of fibrinogen was performed using linear mixed models adjusted for potential confounders. Study-specific results were combined using array-specific meta-analysis, followed by cross-replication of epigenome-wide significant associations. We compared models with and without CRP adjustment to examine the role of inflammation. Results: We identified 208 and 87 significant CpG sites associated with fibrinogen levels from the 450K (p < 1.03 × 10−7) and EPIC arrays (p < 5.78 × 10−8), respectively. There were 78 associations from the 450K array that replicated in the EPIC array and 26 vice versa. After accounting for overlapping sites, there were 83 replicated CpG sites located in 61 loci, of which only 4 have been previously reported for fibrinogen. The examples of genes located near these CpG sites were SOCS3 and AIM2, which are involved in inflammatory pathways. The associations of all 83 replicated CpG sites were attenuated after CRP adjustment, although many remained significant. Conclusion: We identified 83 CpG sites associated with circulating fibrinogen levels. These associations are partially driven by inflammatory pathways shared by both fibrinogen and CRP.

Integrative analysis of genome-wide association studies (GWASs) and gene expression studies in the form of a transcriptome-wide association study (TWAS) has the potential to better elucidate the molecular mechanisms underlying disease etiology. Here we present a method, METRO, that can leverage gene expression data collected from multiple genetic ancestries to enhance TWASs. METRO incorporates expression prediction models constructed in different genetic ancestries through a likelihood-based inference framework, producing calibrated p values with substantially improved TWAS power. We illustrate the benefits of METRO in both simulations and applications to seven complex traits and diseases obtained from four GWASs. These GWASs include two of primarily European ancestry (n = 188,577 and 339,226) and two of primarily African ancestry (n = 42,752 and 23,827). In the real data applications, we leverage gene expression data measured on 1,032 African Americans and 801 European Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study to identify a substantially larger number of gene-trait associations as compared to existing TWAS approaches. The benefits of METRO are most prominent in applications to GWASs of African ancestry where the sample size is much smaller than GWASs of European ancestry and where a more powerful TWAS method is crucial. Among the identified associations are high-density lipoprotein-associated genes including PLTP and PPARG that are critical for maintaining lipid homeostasis and the type II diabetes-associated gene MAPT that supports microtubule-associated protein tau as a key component underlying impaired insulin secretion.

Most existing expression quantitative trait locus (eQTL) mapping studies have been focused on individuals of European ancestry and are underrepresented in other populations including populations with African ancestry. Lack of large-scale well-powered eQTL mapping studies in populations with African ancestry can both impede the dissemination of eQTL mapping results that would otherwise benefit individuals with African ancestry and hinder the comparable analysis for understanding how gene regulation is shaped through evolution. We fill this critical knowledge gap by performing a large-scale in-depth eQTL mapping study on 1,032 African Americans (AA) and 801 European Americans (EA) in the GENOA cohort. We identified a total of 354,931 eSNPs in AA and 371,309 eSNPs in EA, with 112,316 eSNPs overlapped between the two. We found that eQTL harboring genes (eGenes) are enriched in metabolic pathways and tend to have higher SNP heritability compared to non-eGenes. We found that eGenes that are common in the two populations tend to be less conserved than eGenes that are unique to one population, which are less conserved than non-eGenes. Through conditional analysis, we found that eGenes in AA tend to harbor more independent eQTLs than eGenes in EA, suggesting potentially diverse genetic architecture underlying expression variation in the two populations. Finally, the large sample sizes in GENOA allow us to construct accurate expression prediction models in both AA and EA, facilitating powerful transcriptome-wide association studies. Overall, our results represent an important step toward revealing the genetic architecture underlying expression variation in African Americans.

Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy.

BackgroundGenetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants.MethodsWe combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity.FindingsWhen testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P=6.1×10-11; METTL8, rs116951054, MAF 0.09%, P=4.5×10-9; and MATK, rs539182790, MAF 0.05%, P=3.4×10-9). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P=1.2×10-9, nearest gene GATM, and rs71147340, MAF=0.34, P=3.3×10-9, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants.InterpretationThis study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.

Background Exposure to adverse social factors has been associated with an altered inflammatory profile, a risk factor for several acute and chronic diseases. Differential gene expression may be a biological mediator in the relationship. In this study, associations between a range of social factors and expression of inflammation-related genes were investigated. Methods Social factor and gene expression data were collected from 1,264 individuals in the Multi-Ethnic Study of Atherosclerosis (MESA). Inflammation-related genes were identified from the Gene Ontology database. The associations between social factors and gene expression were first assessed using the Global Analysis of Covariance (Global ANCOVA) gene set enrichment test. When the global test was significant, linear regression and elastic net penalized regression were employed to identify the individual gene transcripts within each gene set associated with the social factor. Results Loneliness (p = 0.003), chronic burden (p = 0.002), and major or lifetime discrimination (p = 0.045) were significantly associated with global expression of the chronic inflammatory gene set. Of the 20 transcripts that comprise this gene set, elastic net selected 12 transcripts for loneliness, 8 for chronic burden, and 3 for major or lifetime discrimination. Major or lifetime discrimination was also associated with the inflammatory response (p = 0.029), regulation of the inflammatory response (p = 0.041), and immune response (p = 0.025) gene sets in global analyses, and 53, 136, and 26 transcripts were selected via elastic net for these gene sets respectively. There were no significant associations in linear regression analyses after adjustment for multiple testing. Conclusions This study highlights gene expression as a biological mechanism through which social factors may affect inflammation.

SummaryMetabolic dysregulation in multiple tissues alters glucose homeostasis and influences risk for type 2 diabetes (T2D). To identify pathways and tissues influencing T2D-relevant glycemic traits (fasting glucose [FG], fasting insulin [FI], two-hour glucose [2hGlu] and glycated hemoglobin [HbA1c]), we investigated associations of exome-array variants in up to 144,060 individuals without diabetes of multiple ancestries. Single-variant analyses identified novel associations at 21 coding variants in 18 novel loci, whilst gene-based tests revealed signals at two genes, TF (HbA1c) and G6PC (FG, FI). Pathway and tissue enrichment analyses of trait-associated transcripts confirmed the importance of liver and kidney for FI and pancreatic islets for FG regulation, implicated adipose tissue in FI and the gut in 2hGlu, and suggested a role for the non-endocrine pancreas in glucose homeostasis. Functional studies demonstrated that a novel FG/FI association at the liver-enriched G6PC transcript was driven by multiple rare loss-of-function variants. The FG/HbA1c-associated, islet-specific G6PC2 transcript also contained multiple rare functional variants, including two alleles within the same codon with divergent effects on glucose levels. Our findings highlight the value of integrating genomic and functional data to maximize biological inference.Highlights23 novel coding variant associations (single-point and gene-based) for glycemic traits51 effector transcripts highlighted different pathway/tissue signatures for each traitThe exocrine pancreas and gut influence fasting and 2h glucose, respectivelyMultiple variants in liver-enriched G6PC and islet-specific G6PC2 influence glycemia

To determine whether women who had a hypertensive pregnancy disorder (HPD) have elevated uric acid concentrations decades after pregnancy as compared with women who had normotensive pregnancies.The Genetic Epidemiology Network of Arteriopathy study measured uric acid concentrations in Hispanic (30%), non-Hispanic white (28%), and non-Hispanic black (42%) women (mean age, 60 ± 10 years). This cross-sectional study was conducted between July 1, 2000, and December 31, 2004. Hispanic participants were recruited from families with high rates of diabetes, whereas non-Hispanic participants were recruited from families with high rates of hypertension. This analysis compared uric acid concentrations in women with a history of normotensive (n = 1846) or hypertensive (n = 408) pregnancies by logistic regression.Women who had an HPD had higher uric acid concentrations (median, 5.7 mg/dL vs 5.3 mg/dL; P.001) and were more likely to have uric acid concentrations above 5.5 mg/dL (54.4% vs 42.4%; P = .001) than were women who had normotensive pregnancies. These differences persisted after adjusting for traditional cardiovascular risk factors, comorbidities, and other factors that affect uric acid concentrations. A family-based subgroup analysis comparing uric acid concentrations in women who had an HPD (n = 308) and their parous sisters who had normotensive pregnancies (n = 250) gave similar results (median uric acid concentrations, 5.7 mg/dL vs 5.2 mg/dL, P = 0.02; proportion of women with uric acid concentrations5.5 mg/dL, 54.0% vs 40.3%, P.001).Decades after pregnancy, women who had an HPD have higher uric acid concentrations. This effect does not appear to be explained by a familial predisposition to elevated uric acid concentrations.

The relationship between glycemic control and adverse outcomes found in a population with diabetes has seldom been evaluated in patients with type 2 diabetes. We explored the association between hemoglobin A1c (HbA1c) and hospitalization risks within one-year and eight-year follow-up periods.We conducted a retrospective cohort study on 57,061 patients with type 2 diabetes from National Diabetes Case Management Program during 2002-2004 in Taiwan. HbA1c at baseline and in-hospital mortality, all-cause and cause-specific hospitalization over one year and eight years were analyzed.After multivariate adjustment, one-year risk was higher for cases with HbA1c level6%, 9-10%, ≥10% versus 6-7% for all-cause hospitalization (hazard ratio [HR]: 1.11, 95% confidence interval [CI]: 1.03-1.20; 1.08, 1.01-1.16, and 1.19, 1.12-1.26, respectively) and for ≥10% for diabetes-related hospitalization (1.68, 1.46-1.92). Yet each 1-step increment in HbA1c category (6.0, 6.0-6.9, 7.0-7.9, 8.0-8.9, 9.0-9.9 and ≥10.0%) showed linkage with lower risk of hypoglycemia hospitalization (0.81, 95% CI: 0.74-0.88). For eight-year risk, subjects with HbA1c level6%, and ≥10% were more likely to have in-hospitality mortality (1.16, 1.03-1.31, and 1.23, 1.11-1.35, respectively). Each 1-step increment in HbA1c category showed an association with higher risks of all-cause and diabetes-related hospitalization (1.04, 1.03-1.05, and 1.15, 1.14-1.17, respectively).Higher HbA1c level correlated with lower one-year risk due to hypoglycemia hospitalization but increased one-year and eight-year risks due to all-cause and diabetes-specific hospitalization among Chinese people with type 2 diabetes in Taiwan. Future study must ascertain how to meet HbA1c targets and improve outcome without risk to this population.

Sequencing and exome-chip technologies have motivated development of novel statistical tests to identify rare genetic variation that influences complex diseases. Although many rare-variant association tests exist for case-control or cross-sectional studies, far fewer methods exist for testing association in families. This is unfortunate, because cosegregation of rare variation and disease status in families can amplify association signals for rare variants. Many researchers have begun sequencing (or genotyping via exome chips) familial samples that were either recently collected or previously collected for linkage studies. Because many linkage studies of complex diseases sampled affected sibships, we propose a strategy for association testing of rare variants for use in this study design. The logic behind our approach is that rare susceptibility variants should be found more often on regions shared identical by descent by affected sibling pairs than on regions not shared identical by descent. We propose both burden and variance-component tests of rare variation that are applicable to affected sibships of arbitrary size and that do not require genotype information from unaffected siblings or independent controls. Our approaches are robust to population stratification and produce analytic p values, thereby enabling our approach to scale easily to genome-wide studies of rare variation. We illustrate our methods by using simulated data and exome chip data from sibships ascertained for hypertension collected as part of the Genetic Epidemiology Network of Arteriopathy (GENOA) study.

In summer 2011, the Centers for Disease Control and Prevention Office of Public Health Genomics conducted a stakeholder consultation, administered by the University of Michigan Center for Public Health and Community Genomics, and Genetic Alliance, to recommend priorities for public health genomics from 2012 through 2017. Sixty-two responses from health professionals, administrators, and members of the public were pooled with 2 sets of key informant interviews and 3 discussion groups. NVivo 9 and manual methods were used to organize themes. This review offers an interim analysis of progress with respect to the final recommendations, which demonstrated a strong interest in moving genomic discoveries toward implementation and comparative effectiveness (T3/T4) translational research. A translational research continuum exists with familial breast and ovarian cancer at one end and prostate cancer at the other. Cascade screening for inherited arrhythmia syndromes and hypercholesterolemia lags stakeholder recommendations in the United States but not in Europe; implementation of health service-based screening for Lynch syndrome, and integration into electronic health information systems, is on pace with the recommended timeline. A number of options exist to address deficits in the funding of translational research, particularly for oncogenomic gene expression profiling. The goal of personalized risk assessment necessitates both research progress (eg, in whole genome sequencing, as well as provider education in the differentiation of low- vs high-risk status. The public health approach supports an emphasis on genetic test validation while endorsing clinical translation research inclusion of an environmental and population-based perspective.

ObjectivesThis study sought to identify genetic modifiers of β-blocker response and long-term survival in heart failure (HF).BackgroundDifferences in β-blocker treatment effect between Caucasians and African Americans with HF have been reported.MethodsThis was a prospective cohort study of 2,460 patients (711 African American, 1,749 Caucasian) enrolled between 1999 and 2007; 2,039 patients (81.7%) were treated with a β-blocker. Each was genotyped for β1-adrenergic receptor (ADRB1) Arg389>Gly and G-protein receptor kinase 5 (GRK5) Gln41>Leu polymorphisms, which are more prevalent among African Americans than Caucasians. The primary end point was survival time from HF onset.ResultsThere were 765 deaths during follow-up (median 46 months). β-blocker treatment increased survival in Caucasians (log-rank p = 0.00038) but not African Americans (log-rank p = 0.327). Among patients not taking β-blockers, ADRB1Gly389 was associated with decreased survival in Caucasians (hazard ratio [HR]: 1.98, 95% confidence interval [CI]: 1.1 to 3.7, p = 0.03) whereas GRK5Leu41 was associated with improved survival in African Americans (HR: 0.325, CI: 0.133 to 0.796, p = 0.01). African Americans with ADRB1Gly389Gly GRK5Gln41Gln derived a similar survival benefit from β-blocker therapy (HR: 0.385, 95% CI: 0.182 to 0.813, p = 0.012) as Caucasians with the same genotype (HR: 0.529, 95% CI: 0.326 to 0.858, p = 0.0098).ConclusionsThese data show that differences caused by β-adrenergic receptor signaling pathway gene polymorphisms, rather than race, are the major factors contributing to apparent differences in the β-blocker treatment effect between Caucasians and African Americans; proper evaluation of treatment response should account for genetic variance.

The authors describe the rationale and initial development of a new collaborative initiative, the Genomic Applications in Practice and Prevention Network. The network convened by the Centers for Disease Control and Prevention and the National Institutes of Health includes multiple stakeholders from academia, government, health care, public health, industry and consumers. The premise of Genomic Applications in Practice and Prevention Network is that there is an unaddressed chasm between gene discoveries and demonstration of their clinical validity and utility. This chasm is due to the lack of readily accessible information about the utility of most genomic applications and the lack of necessary knowledge by consumers and providers to implement what is known. The mission of Genomic Applications in Practice and Prevention Network is to accelerate and streamline the effective integration of validated genomic knowledge into the practice of medicine and public health, by empowering and sponsoring research, evaluating research findings, and disseminating high quality information on candidate genomic applications in practice and prevention. Genomic Applications in Practice and Prevention Network will develop a process that links ongoing collection of information on candidate genomic applications to four crucial domains: (1) knowledge synthesis and dissemination for new and existing technologies, and the identification of knowledge gaps, (2) a robust evidence-based recommendation development process, (3) translation research to evaluate validity, utility and impact in the real world and how to disseminate and implement recommended genomic applications, and (4) programs to enhance practice, education, and surveillance.

In order to take into account the complex genomic distribution of SNP variations when identifying chromosomal regions with significant SNP effects, a single nucleotide polymorphism (SNP) association scan statistic was developed. To address the computational needs of genome wide association (GWA) studies, a fast Java application, which combines single-locus SNP tests and a scan statistic for identifying chromosomal regions with significant clusters of significant SNP effects, was developed and implemented. To illustrate this application, SNP associations were analyzed in a pharmacogenomic study of the blood pressure lowering effect of thiazide-diuretics (N=195) using the Affymetrix Human Mapping 100K Set. 55,335 tagSNPs (pair-wise linkage disequilibrium R(2)0.5) were selected to reduce the frequency correlation between SNPs. A typical workstation can complete the whole genome scan including 10,000 permutation tests within 3 hours. The most significant regions locate on chromosome 3, 6, 13 and 16, two of which contain candidate genes that may be involved in the underlying drug response mechanism. The computational performance of ChromoScan-GWA and its scalability were tested with up to 1,000,000 SNPs and up to 4,000 subjects. Using 10,000 permutations, the computation time grew linearly in these datasets. This scan statistic application provides a robust statistical and computational foundation for identifying genomic regions associated with disease and provides a method to compare GWA results even across different platforms.

We investigated the association of 14 polymorphisms in the endothelial nitric oxide synthase gene (NOS3) with ankle brachial index (ABI) in non-Hispanic white hypertensives belonging to hypertensive sibships. Subjects (n=659, mean age 61+/-9 years, 54% women) underwent measurement of ABI using a standard protocol, and the lowest of 4 ABI values was used in the analyses. Non-synonymous SNPs with a minor allele frequency >0.02 and tag SNPs selected based on a measure of linkage disequilibrium (r(2)) were genotyped. We reduced the chance of false positives by testing for replication, randomly selecting 1 hypertensive sib from each sibship to create Subset 1 (n=330) and Subset 2 (n=329). Multivariable linear regression models were used to assess the associations of single NOS3 polymorphisms and haplotypes with ABI after adjustment for covariates (age, sex, body mass index, smoking, total cholesterol, HDL cholesterol, and diabetes). Two specific SNPs in significant LD with each other (rs891512 and rs1808593) were significantly associated with ABI in both subsets. Based on a sliding window approach with a window size of 2, estimated haplotypes from 2 SNP pairs (rs2070744-rs3918226 and rs1808593-rs7830) were also significantly associated with ABI in both subsets. In conclusion, specific NOS3 SNPs and haplotypes were associated with inter-individual variation in ABI, a non-invasive marker of peripheral arterial disease, in replicate subsets of hypertensive subjects. These findings motivate further investigation of the role of NOS3 variants in determining susceptibility to peripheral arterial disease.

To investigate whether novel risk factors, including C-reactive protein (CRP), fibrinogen, lipoprotein(a) [Lp(a)], and homocysteine levels, are associated with the ankle brachial index (ABI) in African American and non-Hispanic white populations and whether novel risk factors account for ethnic differences in peripheral arterial disease (PAD).Between December 2000 and October 2004, original participants in the Genetic Epidemiology Network of Arteriopathy study returned for a second study visit to undergo measurement of risk factors and ABI. The CRP, Lp(a), and homocysteine levels were log transformed to reduce skewness. Multivariable regression analyses were used to assess whether a novel risk factor was associated with ABI after adjustment for conventional risk factors and whether ethnicity was associated with PAD (ABI,or=0.95) after adjustment for conventional and novel risk factors.Of 2229 study participants, the ABI was determined in 1395 African American participants (mean +/- SD age, 63 +/- 9 years; 71% women) and 834 white participants (mean +/- SD age, 58 +/- 9 years; 62% women) who belonged to hypertensive sibships. The mean ABI was lower in African American than in white individuals (0.99 +/- 0.1 vs 1.13 +/- 0.1; P.001). In both ethnic groups, higher levels of CRP, fibrinogen, and homocysteine were each associated with a lower ABI after adjustment for conventional risk factors. In African American participants, the Lp(a) level was also significantly associated with the ABI. African American ethnicity was associated with the presence of PAD after adjustment for conventional risk factors (men: odds ratio [OR], 3.04; 95% confidence interval [CI], 1.80-5.15; women: OR, 2.82; 95% CI, 1.85-4.29), but the risk was significantly attenuated after additional adjustment for novel risk factors (men: OR, 2.11; 95% CI, 1.21-3.70; women: OR, 1.98; 95% CI, 1.26-3.11).Novel risk factors are associated with interindividual variation in ABI in African American and non-Hispanic white populations and partly account for the increased risk of PAD associated with African American ethnicity.

Essential hypertension, defined as elevated levels of blood pressure (BP) without any obvious cause, is a major risk factor for coronary heart disease, stroke, and renal disease. BP levels and susceptibility to development of essential hypertension are partially determined by genetic factors that are poorly understood. Similar to other efforts to understand complex, non-Mendelian phenotypes, genetic dissection of hypertension-related traits employs genomewide linkage analyses of families and association studies of patient cohorts, to uncover rare and common disease alleles, respectively. Family-based mapping studies of elevated BP cover the large intermediate ground for identification of genes with common variants of significant effect. Our genomewide linkage and candidate-gene-based association studies demonstrate that a replicated linkage peak for BP regulation on human chromosome 1q, homologous to mouse and rat quantitative trait loci for BP, contains at least three genes associated with BP levels in multiple samples: ATP1B1, RGS5, and SELE. Individual variants in these three genes account for 2-5-mm Hg differences in mean systolic BP levels, and the cumulative effect reaches 8-10 mm Hg. Because the associated alleles in these genes are relatively common (frequency >5%), these three genes are important contributors to elevated BP in the population at large.

Little is known about the genetics of peripheral arterial disease (PAD). We performed linkage analyses to identify genomic regions that influence ankle–brachial index (ABI), a measure of PAD, in 1310 African Americans (AA) (mean age 62±9 years) and 796 non-Hispanic whites (NHW) (mean age 58±9 years) belonging to hypertensive sibships. ABI was determined at two sites in each lower extremity and the lower of the two average ABIs was used in the analyses after adjustment for age, age 2 , sex, weight, total cholesterol, HDL cholesterol, and ever-smoking. Genotypes were measured at microsatellite marker loci spaced approximately 10cM apart across the 22 autosomes. Heritability was assessed by SOLAR and linkage analyses performed using a variance components approach. Modest heritability ( h 2 ) was noted for the fully adjusted ABI in each ethnic group ( h 2 =0.195, P =0.002 in AA; h 2 =0.212, P =0.006 in NHW). Univariate linkage analyses demonstrated tentative evidence of linkage (multipoint LOD=1.3–2.0) for ABI on chromosomes 1p, 6q, 7q, 10p, and 16p in AA and on chromosome 3p and 3q in NHW. In conclusion, ABI is a modestly heritable trait in AA and NHW hypertensive sibships. Quantitative trait linkage analyses identified several chromosomal regions that may harbor genes influencing ABI.

We measured 381 genomewide markers and performed genetic linkage analyses in search of loci influencing coronary artery calcification (CAC), a measure of atherosclerosis determined by electron beam computed tomography, in 948 non-Hispanic white siblings (mean age [+/-standard deviation] = 59.6 +/- 9.9 years; 73.7% hypertensive). Measured risk factors for atherosclerosis included body mass index, pulse pressure, and high-density lipoprotein (HDL)-cholesterol. After adjustment for sex and age, the logarithm transformed measure of CAC was heritable (0.40 +/- 0.08, P0.0001) and genetically correlated with body mass index (0.28, P0.001), pulse pressure (0.36, P0.001), and HDL-cholesterol (-0.19, P0.001). Univariate linkage analysis demonstrated evidence of linkage for CAC, defined by maximum LOD scores (MLS)or= 1.30, on chromosomes 1p, 4p, 5q, 7p, 13q, and 14q. Bivariate linkage analyses of CAC with each risk factor provided evidence of two regions with pleiotropic effects on CAC and HDL-cholesterol on chromosomes 4p16 (MLS=3.03, P = 0.00084) and 9q12 (MLS = 3.21, P = 0.00056), and of a region with pleiotropic effects on CAC and body mass index on chromosome 17p11 (MLS = 3.04, P = 0.00082). Inasmuch as the chromosome 9 and 17 regions were not detected in the univariate linkage analysis for CAC, multivariate linkage analyses of CAC and genetically correlated risk factors may help localize genes for coronary atherosclerosis.

The objective of this study was to evaluate 1) whether non single nucleotide polymorphisms-coding (non-cSNP) in the apolipoprotein E gene (APOE) identified by resequencing studies contribute to statistically explaining dyslipidemia if variations in the two cSNPs in exon 4 that define the ϵ2, ϵ3, and ϵ4 alleles are ignored, and 2) whether the contribution of these additional SNPs persists when variations in the cSNPs are considered. We used an ecological, multiple-population, data-mining strategy to identify single-SNP and two-SNP genotypes that distinguish between high and low levels of plasma lipids in three training samples, European-Americans from Rochester, MN, African-Americans from Jackson, MS, and Europeans from North Karelia, Finland. We found that a pair of SNPs located in the 5′ region define genotypes A560T832/A560T832, A560T832/A560G832, and A560T832/T560T832, which distinguish between high and low levels of HDL-cholesterol (HDL-C), triglycerides (TG), and/or total cholesterol (T-C). The A560T832/- genotypes predicted high TG and high T-C in both genders in a large independent test sample from Copenhagen, Denmark. Prediction of high T-C in the Danish females was dependent on genotypes defined by the cSNPs. Our study suggests that both regulatory and structural variations should be considered when evaluating the utility of APOE for predicting dyslipidemia in the population at large.

To investigate the accuracy of offspring assessments of parental smoking status, we studied 116 parents and 151 adult children (276 parent-child dyads) who provided data on both their own and their parents' smoking status. All currently smoking and all ex-smoking parents were correctly classified as ever-smokers by their offspring (n = 79 and 100, respectively). Of the 97 offspring who reported on never-smoking parents, 88 correctly classified their parents as never-smokers. Thus, sensitivity for detecting ever-smoking in parents was 100%, and specificity, 91%. Because all incorrect classifications involved never-smoking parents, further analyses focused on this group. Too few parents were misclassified to permit testing of parental characteristics. Offspring who misclassified their parents were significantly older than those who did not; neither sex nor smoking status of the offspring was associated with the increased likelihood of misclassification. No significant differences were discovered for dyadic factors (concordance/discordance for sex; parent-offspring age difference). Overall, these results support the utility of proxy reports of parental smoking phenotype by adult informants when self-report is unavailable.

We have analyzed genetic data for 326 microsatellite markers that were typed uniformly in a large multiethnic population-based sample of individuals as part of a study of the genetics of hypertension (Family Blood Pressure Program). Subjects identified themselves as belonging to one of four major racial/ethnic groups (white, African American, East Asian, and Hispanic) and were recruited from 15 different geographic locales within the United States and Taiwan. Genetic cluster analysis of the microsatellite markers produced four major clusters, which showed near-perfect correspondence with the four self-reported race/ethnicity categories. Of 3,636 subjects of varying race/ethnicity, only 5 (0.14%) showed genetic cluster membership different from their self-identified race/ethnicity. On the other hand, we detected only modest genetic differentiation between different current geographic locales within each race/ethnicity group. Thus, ancient geographic ancestry, which is highly correlated with self-identified race/ethnicity--as opposed to current residence--is the major determinant of genetic structure in the U.S. population. Implications of this genetic structure for case-control association studies are discussed.

Human genetic linkage maps are based on rates of recombination across the genome. These rates in humans vary by the sex of the parent from whom alleles are inherited, by chromosomal position, and by genomic features, such as GC content and repeat density. We have examined--for the first time, to our knowledge--racial/ethnic differences in genetic maps of humans. We constructed genetic maps based on 353 microsatellite markers in four racial/ethnic groups: whites, African Americans, Mexican Americans, and East Asians (Chinese and Japanese). These maps were generated using 9,291 subjects from 2,900 nuclear families who participated in the National Heart, Lung, and Blood Institute-funded Family Blood Pressure Program, the largest sample used for map construction to date. Although the maps for the different groups are generally similar, we did find regional and genomewide differences across ethnic groups, including a longer genomewide map for African Americans than for other populations. Some of this variation was explained by genotyping artifacts--namely, null alleles (i.e., alleles with null phenotypes) at a number of loci--and by ethnic differences in null-allele frequencies. In particular, null alleles appear to be the likely explanation for the excess map length in African Americans. We also found that nonrandom missing data biases map results. However, we found regions on chromosome 8p and telomeric segments with significant ethnic differences and a suggestive interval on chromosome 12q that were not due to genotype artifacts. The difference on chromosome 8p is likely due to a polymorphic inversion in the region. The results of our investigation have implications for inferences of possible genetic influences on human recombination as well as for future linkage studies, especially those involving populations of nonwhite ethnicity.

To assess if the treatment and control of hypertension aggregates in families.The Genetic Epidemiology Network of Arteriopathy (GENOA) study enrolled sibships between 1997 and 1999, including 1329 hypertensive non-Hispanic blacks (1057 sibling pairs) from Jackson, Mississippi, 1133 hypertensive non-Hispanic whites (859 sibling pairs) from Rochester, Minnesota, and 752 hypertensive Hispanic whites (627 sibling pairs) from Starr County, Texas. Hypertension awareness and drug treatment were ascertained at examination; control was defined by blood pressure levels140/90 mm Hg. As a measure of familial aggregation, odds ratios were calculated to assess concordance between sibling pairs in the treatment and control of hypertension.Overall, 90.5% of subjects were aware of their hypertension; 90.6% of those who were aware were treated with antihypertensive drugs and 56.0% of those treated had their hypertension controlled. There was statistically significant sib-sib concordance in the treatment of hypertension (odds ratio [OR] = 1.61; 95% confidence interval [CI]: 1.25 to 2.47; P = 0.003) and in the control of drug-treated hypertension (OR = 1.51; 95% CI: 1.25 to 1.81; P0.0001).These findings suggest that the treatment and control of hypertension aggregates in families.

Family history is a powerful predictor of variation in risk of common diseases and conditions because it can represent the influence of both shared genes and shared environments. To investigate the relationship of parental smoking history with nicotine dependence and smoking rate, as well as with known psychological cofactors for smoking (depression, anxiety, alcoholism, disordered eating), we studied smoking adults who provided smoking history for both parents. We found that having two ever-smoking parents, in comparison to zero or one, was associated with higher nicotine dependence scores, cigarettes per day, and levels of anxiety in participant, with a trend for depression. Participants whose mothers smoked during pregnancy had significantly higher scores on nicotine dependence, smoking rate, and disordered eating than participants with either ever-smoking mothers who did not smoke during pregnancy or never-smoking mothers. These findings suggest that family history of smoking may be a key determinant of interindividual variation in smoking behavior, nicotine dependence, and psychological cofactors among smokers.

The distribution of plasma lipoprotein[a] (Lp[a] ) concentrations, a risk factor for cardiovascular disease, varies greatly among racial groups, with African Americans having values that are shifted toward higher levels than those of whites. The underlying cause of this heterogeneity is unknown, but a role for "trans-acting" factors has been hypothesized. This study used genetic linkage analysis to localize genetic factors influencing Lp[a] levels in African Americans that were absent in other populations; linkage results were analyzed separately in non-Hispanic whites, Hispanic whites, and African Americans. As expected, all three samples showed highly significant linkage at the approximate location of the lysophosphatidic acid locus. The white populations also independently had regions of significant linkage on chromosome 19 (LOD 3.80) and suggestive linkage on chromosomes 12 (LOD 1.60), 14 (LOD 2.56), and 19 (LOD 2.52).? No linkage evidence was found to support the hypothesis of another single gene with large effects specifically segregating in African Americans that may account for their elevated Lp[a] levels.-Barklej, R. A., A. C. Brown, C. L. Hanis, S. L. Kardia, S. T. Turner, and E. Boerwinkle. Lack of genetic linkage evidence for a trans-acting factor having a large effect on plasma lipoprotein[a] levels in African Americans.

Cytokeratins. (CK) are intermediate filaments whose expression is often altered in epithelial cancer. Systematic identification of lung adenocarcinoma proteins using two-dimensional polyacrylamide gel electrophoresis and mass spectrometry has uncovered numerous CK isoforms. In this study, 93 lung adenocarcinomas. (64 stage I and 29 stage III) and 10 uninvolved lung samples were quantitatively examined for protein expression. Fourteen of 21 isoforms of CK 7, 8, 18, 19 occurred at significantly higher levels. (P

The atherosclerotic process begins in childhood but, in general, does not reach the clinical horizon until after the fifth decade of life, at which point the best opportunities for prevention and intervention have been lost. In order to identify children with a high risk of developing coronary artery disease (CAD), risk factors measured in children that are the most informative indicators of future risk must be identified. Using a novel analytical strategy that incorporates a continuum of information about context dependency, we investigated whether there were significant differences in intermediate biochemical and physiological traits between children (189 females and 188 males, ages 5–20.5 years) with and without a strong family history of clinically-defined CAD at three levels of context dependency (coarse grain, medium grain, and fine grain). In the coarse-grained analysis we tested for differences in mean levels of nine intermediate traits (lipids, apolipoproteins, blood pressure traits) and indices of external and internal environmental context (age, body mass index, smoking status). Female children with a strong family history had higher average levels for total cholesterol, triglyceride, Apo B, and systolic blood pressure and were on average older and weighed more than female children with a weak family history of CAD. Male children with a strong family history of CAD had higher average levels of triglycerides and were on average older than male children with a weak family history. In the medium-grained analysis we investigated whether the regression relationships between each intermediate trait and each measure of environmental context was significantly different between children with and without a strong family history of CAD. Our results indicate that children with a strong family history of CAD have a significantly different relationship between their intermediate traits and environmental contexts than children with a weak family history. In the fine-grained analysis, we stratified the sample into age, BMI, and smoking subgroups and tested for mean differences in the intermediate traits between children with and without a strong family history. For seven of the nine intermediate traits we found evidence of significant mean differences between children with and without a strong family history of CAD in particular age and BMI subgroups in nonsmokers that were not expected given the results from separate age-dependent or BMI-dependent marginal analyses. From these analyses, we conclude that the inferences about intermediate biochemical and physiological trait associations with family history of CAD depend on where on the coarse-grain to fine-grain continuum of context dependency the analysis is performed. In many cases, inferences at one level of investigation are different than the inferences made at a coarser or finer level. This study documents the complexity of the associations between intermediate traits and risk of CAD and raises the question of how many models are needed to maximize disease prediction and where these models should fall on the coarse- to fine-grain continuum.

Objective Hyperhomocysteinemia is associated with an elevated cardiovascular disease risk. We examined whether women with a history of hypertension in pregnancy are more likely to have a high level of serum homocysteine decades after pregnancy. Study Design Serum homocysteine was measured at a mean age of 60 years in nulliparous women (n = 216), and women with a history of normotensive (n = 1825) or hypertensive (n = 401) pregnancies who participated in the Genetic Epidemiology Network of Arteriopathy (GENOA) study. Relationships between homocysteine and pregnancy history were examined by linear and logistic regression, controlling for multiple covariates including personal and family history of hypertension, diabetes, obesity, tobacco use, and demographics. Results A history of hypertension in pregnancy, when compared with normotensive pregnancy, was associated with a 4.5% higher serum homocysteine level ( P = .015) and 1.60-fold increased odds of having an elevated homocysteine (95% confidence interval, 1.15–2.21; P = .005) after adjusting for potentially confounding covariates. In contrast, a history of normotensive pregnancy, as compared with nulliparity, was associated with a 6.1% lower serum homocysteine level ( P = .005) and a 0.49-fold reduced odds of elevated homocysteine levels (95% confidence interval, 0.32–0.74; P Conclusion Homocysteine levels decades after pregnancy are higher in women with a history of pregnancy hypertension, even after controlling for potential confounders. Thus, pregnancy history may prompt homocysteine assessment and risk modification in an attempt at primary prevention of cardiovascular disease.