Association of HNF4α gene polymorphisms with susceptibility to type 2 diabetes

Abstract

The present study aimed to explore the association between single nucleotide polymorphisms (SNPs) in the hepatocyte nuclear factor‑4α (HNF‑4α) gene and the incidence of type 2 diabetes in the Chinese Bai population in Dali city, China. The polymerase chain reaction‑restriction fragment length polymorphism method was used to analyze four SNPs (rs4810424, rs1884613, rs1884614 and rs2144908) in the HNF‑4α gene in 44 patients with type 2 diabetes and 87 healthy controls in Chinese Bai individuals. The haploid type was subsequently built to assess its association with the incidence of type 2 diabetes in the Bai population in Dali city. No significant differences were observed between the genotype and allele frequencies of the four SNPs in the HNF‑4α gene and type 2 diabetes mellitus (P>0.05). However, the frequency of haplotype, CCTA, built by rs4810424, rs1884613, rs1884614 and rs2144908 was significantly higher in the type 2 diabetes mellitus group compared with the control group (χ2=8.34, P=0.004). The four polymorphisms, rs4810424, rs1884613, rs1884614 and rs2144908, in the HNF‑4α gene were not the susceptible loci for type 2 diabetes in the Bai population of Dali city, however, the haplotype, CCTA, built from the four SNPs may increase the risk of type 2 diabetes in this population.

Microbiota regulate intestinal epithelial gene expression by suppressing the transcription factor Hepatocyte nuclear factor 4 alpha

“…5). In addition to IBD, human HNF4A variants are associated with metabolic syndrome (Weissglas-Volkov et al 2006) and type 2 diabetes (Ma et al 2016). Interestingly, microbiota have also been implicated in both of these diseases (Qin et al 2012;Vrieze et al 2012), raising the possibility that microbiota suppression of HNF4A trans activity could play a role in these diseases as well.…”

Genetic associations between Transcription Factor 7 Like 2 rs7903146 polymorphism and type 2 diabetes mellitus: a meta-analysis of 115,809 subjects

“…Therefore, our results were derived from unadjusted estimations, and failure to conduct further adjusted analyses for baseline characteristics of participants such as age, gender and co-morbidity conditions may influence the veracity of our findings [20, 21]. Secondly, significant heterogeneities were detected in certain subgroup comparisons, which indicated that the inconsistent results of included studies could not be fully explained by differences in ethnic background, and other unmeasured characteristics of participants may also partially attribute to between-study heterogeneities [22]. Thirdly, since only published articles were eligible for analyses, although funnel plots revealed no obvious publication biases, we still could not rule out the possibility of potential publication biases [23].…”

Genetic variants in promoter regions associated with type 2 diabetes mellitus: A large‐scale meta‐analysis and subgroup analysis

“…The results were consistent with previous studies that promoter variants rs266729 and rs17300539 polymorphisms in ADIPOQ gene, rs2144908 and rs4810424 polymorphisms in HNF4A gene were associated with T2D risk. Silvia 58 reported that the risk allele of rs1884614 of HNF-4A was significantly associated with increased risk of T2D, while no significant association in our analysis when new publications 19,[62][63][64][65] were included. Silvia also reported that the risk allele of rs1884613 of HNF4A was significantly associated with increased risk of T2D, it was significantly associated with increased risk of T2D when the HWE deviation excluded only.…”

“…Some association studies of genetic variants in promoter region and T2D risk have been reported . However, previous studies were limited to small number of individual genetic variants and insufficient sample size . In addition, effects of the study populations and demographic characteristics were often neglected.…”

“…16,17 However, previous studies were limited to small number of individual genetic variants and insufficient sample size. [18][19][20] In addition, effects of the study populations and demographic characteristics were often neglected. In this study, we conducted a largescale meta-analysis and subgroup analysis of T2D associated genetic variants in promoter regions to confirm their contribution to the susceptibility in T2D.…”