ArticleMolecular biology reports2014
Association study of common variations of FBN1 gene and essential hypertension in Han Chinese population.
Article in Molecular biology reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed, 5 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fibrillin-1 (FBN1) was reported to have impact on the physiological arterial stiffness and vascular remodeling with hypertension of recent years. In the previous study we reported the association of four functional single nucleotide polymorphisms (SNPs) of FBN1 gene and hypertension. Here, we further investigate the association of four tagging SNPs (tagSNPs) which covered remain genetic variation blocks of FBN1 gene with hypertension, blood pressure and efficacy of antihypertensive in a South Han Chinese population. A case-control study including 2,012 hypertension cases and 2,116 controls age- and sex-matched controls was conducted from a community-based population and four candidate tagSNPs of the FBN1 gene were genotyped. Association analysis by multiple logistic regression was conducted for allele, genotype and haplotype and hypertension, blood pressure trait and control status with antihypertensive. General linear model was applied to compare blood pressure levels between genotypes. The association of rs17361868 and hypertension was statistically significant and that was further observed in female, ≥55 years, non-smoking and non-drinking populations (P < 0.05). Significant association of rs668842, rs11635140 and hypertension were observed in <55 years population as well as the later in female and non-smoking populations respectively. Haplotype G-T constructed of rs668842 and rs11635140 was significantly associated with hypertension comparing to reference haplotype A-C (P = 0.022). Normally distributed square root of TGF-β1 (pg/ml) of hypertension cases (148.56 ± 66.46) was significantly higher than that of control (128.52 ± 65.11), P = 0.008. Furthermore, TGF-β1 was significantly correlated with SBP (r = 0.135, P = 0.018) and DBP (r = 0.154, P = 0.007) respectively whereas no statistical difference of blood pressure or TGF-β1 was observed between genotypes. Remarkably, rs17361868 were significantly associated with the status of blood pressure in the patients taking three of the antihypertensive drugs, Zhen Ju Jiang Ya tablets, Jiang Ya tablet and compound reserpine (P < 0.05). The present study provides further association evidence of FBN1 gene polymorphisms and hypertension, antihypertensive efficacy. Further replication of these results via association or prospective studies conducted in other populations is warranted.
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.