Evidence map›Paper›PMID 37226099›Full record

ArticleBMC cardiovascular disorders2023

Association of MLL3 and TGF-β signaling gene polymorphisms with the susceptibility and prognostic outcomes of Stanford type B aortic dissection : MLL3 with TGF-β signal pathway association with Stanford type B AD.

Qinghua Yuan, Yafei Chang, Peipei Jiang, Ling Sun, Yitong Ma, Xiang Ma

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Article in BMC cardiovascular disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors at 4 institutions in 1 country.

Qinghua Yuan *Department of Cardiology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Yafei Chang *Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
Peipei JiangDepartment of Geriatrics, The Fourth People's Hospital of Urumqi City, Urumqi, China.
Ling SunDepartment of Cardiology, Fuyang Tumor hospital, Fuyang, China.
Yitong MaDepartment of Cardiology, First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Xiang MaDepartment of Cardiology, First Affiliated Hospital of Xinjiang Medical University, Urumqi, China. maxiangxj@yeah.net.
Sun Yat-sen University · CNXinjiang Medical University · CNFuyang Maternity and Child Health Care Hospital · CNThe Fourth People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aims to investigate the association of lysine methyltransferase 2 C (MLL3) and transforming growth factor β (TGF-β) signaling-related gene polymorphisms with the susceptibility of Stanford type B aortic dissection (AD) and its clinical prognostic outcomes. The methods involved investigating the MLL3 (rs10244604, rs6963460, rs1137721), TGFβ1 (rs1800469), TGFβ2 (rs900), TGFR1 (rs1626340) and TGFR2 (rs4522809) gene polymorphisms. Logistic regression was performed to investigate the association between 7 single nucleotide gene polymorphisms (SNPs) and Stanford type B aortic dissection. The GMDR software was used to analyze gene-gene and gene-environment interactions. The odds ratio (OR) with a 95% confidence interval (CI) was employed to evaluate the association of genes and Stanford type B AD risk.

resultsGenotypes and allele distributions in the case and control groups showed significant differences (P < 0.05). Logistic regression has shown that the Stanford Type B AD risk was highest in individuals with the rs1137721 CT genotype (OR = 4.33, 95% CI = 1.51-12.40). Additionally, WBC, drinking, hypertension, triglycerides (TG), and low-density lipoprotein (LDL-C) were independent risk factors for Stanford Type B AD. Logistic regression showed that the Stanford Type B AD risk was highest in individuals with the MLL3 (rs1137721)-TT + CT and TGFβ1 (rs4522809)-AA genotype (OR = 6.72, 95% CI = 1.56-29.84), and lowest in those with the MLL3 (rs1137721)-CC and TGFβ1 (rs4522809)-AA + GG genotype (OR = 4.38, 95% CI = 0.92-20.83). However, the 55-month median long-term follow-up did not show statistical significance.

conclusionCarriers of both TT + CT of MLL3 (rs1137721) and AA of TGFβ1 (rs4522809) polymorphisms may be closely related to the development of Stanford type B AD. MLL3 (rs1137721), WBC, and TG/TC were found to be associated with the morbidity of Stanford type B AD. MLL3 (KMT2C) is associated with the TGF-β signaling pathway protein. The risk of Stanford type B AD is related to the interactions of gene-gene and gene-environment.

Indexed as

Aortic DissectionDNA-Binding ProteinsTransforming Growth Factor beta1HumansPolymorphism, Single NucleotidePrognosisSignal TransductionDNA-Binding ProteinsKMT2C protein, humanTGFB1 protein, humanTransforming Growth Factor beta1MLL3Stanford type B ADTGFβ signal pathway

Identifiers

PMID37226099
PMCPMC10210388
OpenAlexW4378070717

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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.