Rare variants in fox-1 homolog A (RBFOX1) are associated with lower blood pressure

He, Karen Y.; Wang, Heming; Cade, Brian E.; Nandakumar, Priyanka; Giri, Ayush; Ware, Erin B.; Haessler, Jeffrey; Liang, Jingjing; Smith, Jennifer A.; Franceschini, Nora; Le, Thu H.; Kooperberg, Charles; Edwards, Todd L.; Kardia, Sharon L.R.; Lin, Xihong; Chakravarti, Aravinda; Redline, Susan; Zhu, Xiaofeng

doi:10.1371/journal.pgen.1006678

Cited by 20 publications

(31 citation statements)

References 61 publications

(54 reference statements)

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“…Consistent with this evidence, to date, variants in Mendelian HTN syndromes, do not explain the variance of BP in the general population. Although linkage studies are often considered to have low statistical power, many disease variants have been identified through linkage analysis, such as the BRCA1 and BRCA2 genes for breast cancer and RBFOX1 for BP [48,49]. We used LOD score > 3, the initial proposal by Morton [25], as our genome-wide significance level corresponding to a principled posterior probability of linkage of 95 percent (Ott 1991 [26], p.66).…”

Section: Discussionmentioning

confidence: 99%

Combined linkage and association analysis identifies rare and low frequency variants for blood pressure at 1q31

et al. 2018

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High blood pressure (BP) is a major risk factor for cardiovascular disease (CVD) and is more prevalent in African Americans as compared to other US groups. Although large, population-based genome-wide association studies (GWAS) have identified over 300 common polymorphisms modulating inter-individual BP variation, largely in European ancestry subjects, most of them do not localize to regions previously identified through family-based linkage studies. This discrepancy has remained unexplained despite the statistical power differences between current GWAS and prior linkage studies. To address this issue, we performed genome-wide linkage analysis of BP traits in African-American families from the Family Blood Pressure Program (FBPP) and genotyped on the Illumina Human Exome BeadChip v1.1. We identified a genomic region on chromosome 1q31 with LOD score 3.8 for pulse pressure (PP), a region we previously implicated in DBP studies of European ancestry families. Although no reported GWAS variants map to this region, combined linkage and association analysis of PP identified 81 rare and low frequency exonic variants accounting for the linkage evidence. Replication analysis in eight independent African ancestry cohorts (N = 16,968) supports this specific association with PP (P = 0.0509). Additional association and network analyses identified multiple potential candidate genes in this region expressed in multiple tissues and with a strong biological support for a role in BP. In conclusion, multiple genes and rare variants on 1q31 contribute to PP variation. Beyond producing new insights into PP, we demonstrate how family-based linkage and association studies can implicate specific rare and low frequency variants for complex traits.

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Section: Discussionmentioning

confidence: 99%

Combined linkage and association analysis identifies rare and low frequency variants for blood pressure at 1q31

et al. 2018

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“…Rbfox1 (RNA-binding protein fox-1) is the associated gene of lncRNA 1700123O21Rik. He et al identified that rare, exonic variants in Rbfox1 had protective effects on BP traits, which could be important in searching new drugs for cardiovascular disease [ 26 ]. Hence, Rbfox1 is expressed in multiple tissues that may relate to blood pressure, and the identification of these rare coding variants will facilitate precision medicine in treating cardiovascular disease.…”

Section: Discussionmentioning

confidence: 99%

Microarray Analysis Reveals a Potential Role of lncRNA Expression in 3,4-Benzopyrene/Angiotensin II-Activated Macrophage in Abdominal Aortic Aneurysm

Zhou

Wang

Xue

et al. 2017

Stem Cells International

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Abdominal aortic aneurysm (AAA) is a fatal disease, and exposure to 3,4-benzopyrene (Bap) is closely related to the development of AAA. We have found that Bap could impair the biological function of endothelial progenitor cells (EPCs), which are associated with the occurrence of AAA. We have also demonstrated that macrophage activation plays a key role in Bap-induced AAA, but the mechanism is unknown. Here, we used a mouse lncRNA array to investigate the expression signatures of lncRNAs and mRNAs in Bap-activated macrophage. A total of 457 lncRNAs and 219 mRNAs were found to be differentially expressed. The function of differential mRNAs was determined by pathway and Gene Ontology analysis. Eight pathways associated with inflammation were upregulated, and seven pathways including cell apoptosis were downregulated. It was worth noting that AGE-RAGE pathway, which was involved in Bap-induced EPC dysfunction, was significantly upregulated in Bap-activated macrophage and may contribute to AAA formation. Thus, lncRNAs may exert a key role in activated macrophages and intervene the core lncRNAs and may inhibit the occurrence of a series of cascade reactions in the macrophages, which may provide potential targets for AAA caused by smoking.

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“…4,5,6 For example, Igartua et al 7 identified two novel rare variants associated with low-density lipoprotein cholesterol and high-density lipoprotein cholesterol with larger effects than the previously discovered variants within the known blood lipid associated loci. In another study by He et al, 8 multiple rare variants were found to be associated with lower systolic blood pressure. Successes from rare variant association studies highlight the importance of rare variants to complex disease susceptibility.…”

Section: Introductionmentioning

confidence: 91%

A unified method for rare variant analysis of gene-environment interactions

Lim

Chen

Dupuis

et al. 2019

Preprint

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Advanced technology in whole-genome sequencing has offered the opportunity to comprehensively investigate the genetic contribution, particularly rare variants, to complex traits. Many rare variants analysis methods have been developed to jointly model the marginal effect but methods to detect gene-environment (GE) interactions are underdeveloped. Identifying the modification effects of environmental factors on genetic risk poses a considerable challenge. To tackle this challenge, we develop a unified method to detect GE interactions of a set of rare variants using generalized linear mixed effect model. The proposed method can accommodate both binary and continuous traits in related or unrelated samples. Under this model, genetic main effects, sample relatedness and GEinteractions are modeled as random effects. We adopt a kernel-based method to leverage the joint information across rare variants and implement variance component score tests to reduce the computational burden. Our simulation study shows that the proposed method maintains correct type I error rates and high power under various scenarios, such as differing the direction of main genotype and GE interaction effects and the proportion of causal variants in the model for both continuous and binary traits. We illustrate our method to test gene-based interaction with smoking on body mass index or overweight status in the Framingham Heart Study and replicate the CHRNB4 gene association reported in previous large consortium meta-analysis of single nucleotide polymorphism (SNP)-smoking interaction. Our proposed set-based GE test is computationally efficient and is applicable to both binary and continuous phenotypes, while appropriately accounting for familial or cryptic relatedness.

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Rare variants in fox-1 homolog A (RBFOX1) are associated with lower blood pressure

Cited by 20 publications

References 61 publications

Combined linkage and association analysis identifies rare and low frequency variants for blood pressure at 1q31

Combined linkage and association analysis identifies rare and low frequency variants for blood pressure at 1q31

Microarray Analysis Reveals a Potential Role of lncRNA Expression in 3,4-Benzopyrene/Angiotensin II-Activated Macrophage in Abdominal Aortic Aneurysm

A unified method for rare variant analysis of gene-environment interactions

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