ArticleAmerican journal of hypertension2015
Single nucleotide polymorphism-single nucleotide polymorphism interactions among inflammation genes in the genetic architecture of blood pressure in the Framingham Heart Study.
Article in American journal of hypertension, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Direct simulation of hypertensive stress on endothelial cells: a streamlined model of in-vitro-hypertension.Frontiers in physiology · 2025Article
- Effects of Reducing the South and Reinforcing the North Method on Inflammatory Injury Induced by Hyperlipidemia.Evidence-based complementary and alternative medicine : eCAM · 2021Article
- Neuroimmune crosstalk in the pathophysiology of hypertension.Nature reviews. Cardiology · 2019Review
- Variations in ADIPOR1 But Not ADIPOR2 are Associated With Hypertriglyceridemia and Diabetes in an Admixed Latin American Population.The review of diabetic studies : RDS · 2017Article
- Influence of Smoking Status and Intensity on Discovery of Blood Pressure Loci Through Gene-Smoking Interactions.Genetic epidemiology · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundHypertension is a major global health burden, but, although systolic and diastolic blood pressure (BP) each have estimated heritability of at least 30%, <3% of their variance has been attributed to particular genetic variants. Few studies have shown interactions between pairs of single nucleotide polymorphisms (SNPs) to be associated with BP. Although many studies use a Bonferroni correction for multiple testing to control type I error, thereby potentially reducing power, false discovery rate (FDR) approaches are also used in genome-wide studies. Renal ion balance genes have been associated with BP regulation, but, although inflammation has been studied in connection with BP, few studies have reported associations between inflammation genes and BP.
methodsWe analyzed SNP-SNP interactions among 31 SNPs from genes involved in renal ion balance and 30 SNPs from genes involved in inflammation using data from the Framingham Heart Study.
resultsNo evidence of association was found for interactions among renal ion balance SNPs for either systolic or diastolic BP. A group of 3 interactions involving 6 inflammation genes (IKBKB-NFKBIA, IKBKE-CHUK, and ADIPOR2-RETN) showed evidence of association with diastolic BP with an FDR of 4.2%; no single interaction reached experiment-wide significance.
conclusionsThis study identified promising and biologically plausible candidates for interactions between inflammation genes that may be associated with DBP. Analysis using the FDR may allow detection of signals in the presence of modest noise (false positives) that a stringent approach based on Bonferroni-corrected P value thresholds may miss.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.