Gene-Education Interactions Identify Novel Blood Pressure Loci in the Framingham Heart Study

Basson, Jacob; Sung, Yun Ju; Schwander, Karen; Kume, Rezart; Simino, Jeannette; Fuentes, Lisa de las; Rao, D. C.

doi:10.1093/ajh/hpt283

Cited by 19 publications

(16 citation statements)

References 40 publications

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“…BP is known to be modulated by a variety of lifestyle factors, such as diet [21], exercise [22], and smoking [23], as well as other factors such as age [24, 25] and obesity [26]. In GWAS for HTN-related phenotypes, significant GxE interactions have been identified with alcohol consumption [27], body mass index (BMI) [28], smoking [29, 30], education levels [31], and sodium intake [46] which are all modifiable through lifestyle changes. These findings suggest that further investigation into GxE interaction may identify causal genetic loci that contribute to missing heritability [33].…”

Section: Introductionmentioning

confidence: 99%

A Review of the Genetics of Hypertension with a Focus on Gene-Environment Interactions

2017

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Purpose of review Here, we discuss the interpretation and modeling of gene-environment interactions in hypertension related phenotypes, with a focus on the necessary assumptions and possible challenges. Recent findings Recently, small cohort studies have discovered several novel genetic variants associated with hypertension-related phenotypes through modeling gene-environment interactions. Several consortia-based meta-analytic efforts have uncovered many novel genetic variants in hypertension without modeling interaction terms, giving promise to future meta-analytic efforts that incorporate gene-environment interactions. Summary Heritability studies and genome-wide association studies have established that hypertension, a prevalent cardiovascular disease, has a genetic component that may be modulated by the environment (such as lifestyle factors). This review includes a discussion of known genetic associations for hypertension/blood pressure, including those resulting from the incorporation of gene-environmental interaction modeling.

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Section: Introductionmentioning

confidence: 99%

A Review of the Genetics of Hypertension with a Focus on Gene-Environment Interactions

2017

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“…; Basson et al. ; Reiter et al. ) and the BP response to pharmacotherapy (Maitland‐van der Zee et al.…”

Section: Introductionmentioning

confidence: 99%

Deep-targeted exon sequencing reveals renal polymorphisms associate with postexercise hypotension among African Americans

et al. 2016

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We found variants from the Angiotensinogen‐Converting Enzyme (ACE), Angiotensin Type 1 Receptor (AGTR1), Aldosterone Synthase (CYP11B2), and Adducin (ADD1) genes exhibited intensity‐dependent associations with the ambulatory blood pressure (BP) response following acute exercise, or postexercise hypotension (PEH). In a validation cohort, we sequenced exons from these genes for their associations with PEH. Obese (30.9 ± 3.6 kg m−2) adults (n = 23; 61% African Americans [AF], 39% Caucasian) 42.0 ± 9.8 years with hypertension (139.8 ± 10.4/84.6 ± 6.2 mmHg) completed three random experiments: bouts of vigorous and moderate intensity cycling and control. Subjects wore an ambulatory BP monitor for 19 h. We performed deep‐targeted exon sequencing using the Illumina TruSeq Custom Amplicon kit. Variant genotypes were coded as number of minor alleles (#MA) and selected for further statistical analysis based upon Bonferonni or Benjamini–Yekutieli multiple testing corrected p‐values under time adjusted linear models for 19 hourly BP measurements per subject. After vigorous intensity over 19 h among ACE,AGTR1,CYP11B2, and ADD1 variants passing multiple testing thresholds, as the #MA increased, systolic (SBP) and/or diastolic BP decreased 12 mmHg (P = 4.5E‐05) to 30 mmHg (P = 6.4E‐04) among AF only. In contrast, after moderate intensity over 19 h among ACE and CYP11B2 variants passing multiple testing thresholds, as the #MA increased, SBP increased 21 mmHg (P = 8.0E‐04) to 22 mmHg (P = 8.2E‐04) among AF only. In this replication study, ACE,AGTR1,CYP11B2, and ADD1 variants exhibited associations with PEH after vigorous, but not moderate intensity exercise among AF only. Renal variants should be explored further with a multi‐level “omics” approach for associations with PEH among a large, ethnically diverse sample of adults with hypertension.

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“…Additionally, clinical biobanks that contain biological samples linked to EHRs are becoming an invaluable resource for conducting genetic epidemiology studies. Despite the potential for EHRs in research settings, these clinical data repositories currently have noted deficits in the availability and completeness of important social and environmental data 17 , including SES, that are known to contribute independently to health status and could modify genetic effects 18 .…”

Section: Introductionmentioning

confidence: 99%

Development and Performance of Text-Mining Algorithms to Extract Socioeconomic Status From De-Identified Electronic Health Records

et al. 2016

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Socioeconomic status (SES) is a fundamental contributor to health, and a key factor underlying racial disparities in disease. However, SES data are rarely included in genetic studies due in part to the difficultly of collecting these data when studies were not originally designed for that purpose. The emergence of large clinic-based biobanks linked to electronic health records (EHRs) provides research access to large patient populations with longitudinal phenotype data captured in structured fields as billing codes, procedure codes, and prescriptions. SES data however, are often not explicitly recorded in structured fields, but rather recorded in the free text of clinical notes and communications. The content and completeness of these data vary widely by practitioner. To enable gene-environment studies that consider SES as an exposure, we sought to extract SES variables from racial/ethnic minority adult patients (n=9,977) in BioVU, the Vanderbilt University Medical Center biorepository linked to de-identified EHRs. We developed several measures of SES using information available within the de-identified EHR, including broad categories of occupation, education, insurance status, and homelessness. Two hundred patients were randomly selected for manual review to develop a set of seven algorithms for extracting SES information from de-identified EHRs. The algorithms consist of 15 categories of information, with 830 unique search terms. SES data extracted from manual review of 50 randomly selected records were compared to data produced by the algorithm, resulting in positive predictive values of 80.0% (education), 85.4% (occupation), 87.5% (unemployment), 63.6% (retirement), 23.1% (uninsured), 81.8% (Medicaid), and 33.3% (homelessness), suggesting some categories of SES data are easier to extract in this EHR than others. The SES data extraction approach developed here will enable future EHR-based genetic studies to integrate SES information into statistical analyses. Ultimately, incorporation of measures of SES into genetic studies will help elucidate the impact of the social environment on disease risk and outcomes.

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Gene-Education Interactions Identify Novel Blood Pressure Loci in the Framingham Heart Study

Abstract: PTN and TOX2 are associated with BP. Analyzing SNP-education interactions may detect novel associations. Education may be a surrogate for unmeasured exposures and behaviors modifying SNP effects on BP.

Cited by 19 publications

References 40 publications

A Review of the Genetics of Hypertension with a Focus on Gene-Environment Interactions

A Review of the Genetics of Hypertension with a Focus on Gene-Environment Interactions

Deep-targeted exon sequencing reveals renal polymorphisms associate with postexercise hypotension among African Americans

Development and Performance of Text-Mining Algorithms to Extract Socioeconomic Status From De-Identified Electronic Health Records

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