Genetic Predisposition for Type 2 Diabetes Mellitus in a Cameroonian Population: Contribution of rs4731702 (C/T) Polymorphism of Krüppel-Like Factor 14 Gene

Introduction: Krüppel Like Factor 14 (KLF14) gene has recently been identified as a master gene for multiple metabolic phenotypes. The aim of the research study was to investigate the relationship between KLF14 rs4731702 (C/T) gene polymorphism with Type 2 Diabetes Mellitus (T2DM) in a Cameroonian population. Patients and Methods: This case-control study was conducted in 85 patients with T2DM and 95 healthy normoglycemic controls. All were nonrelated, of Cameroonian origin, and were adults aged 24 years old and above. Demographic, clinical and biological data were collected, and biochemical explorations were performed using enzymatic colorimetric methods. The genotyping of KLF14 rs4731702 (CT) gene polymorphism was done by the Polymerase Chain Reaction and Restriction Fragment Length Polymorphism. Results: In comparing the Cameroonian population that consisted of 85 patients with T2DM and 95 healthy controls, the minor or risk allele of the rs4731702 (C/T) polymorphism of the KLF14 gene was T (63.53% diabetic patients vs. 26.32% healthy controls, OR = 4.877 and p < 0.0001) while the protective allele was C (36.47% diabetic patients vs. 73.68% healthy controls, OR = 0.205 and p < 0.0001). The susceptibility to T2DM was higher among subjects having the CT and TT genotypes with OR = 2.721 and p = 0.0145) and OR = 3.907 and p < 0.0001) respectively. This gene polymorphism was not preferentially associated with a specific diabetes phenotype. Conclusion: This study has demonstrated for the first time the relationship between the KLF14 rs4731702 (C/T) gene polymorphism and T2DM in this Cameroonian population. This gene polymorphism could be a promising target for personalized medicine through the development of clinical genetic testing.


Introduction
Type 2 Diabetes Mellitus (T2DM) is a polygenic metabolic disease, the most common form (more than 90%) is that in which insulin resistance and deficiency lead to high blood glucose levels due to the fact that in this state, the body produces insulin but becomes resistant to it so that it is ineffective [1]. In 2019, there were more than 350 million adult persons at high risk of developing diabetes, in the same year, 463 million adults had diabetes and by 2045 this number is projected to get to 700 million. In this period of time, sub-Saharan Africa will experience a 143% increase from 19 million in 2019 to 47 million in 2045. It remains one of the major public health problems with an increase in social and economic burdens in both low-income and high-income countries [2].
T2DM is a complex multifactorial disease. Including toxins, stress, diet, obesity, sedentary lifestyle, small or large birth weight and physical inactivity as environmental factors and many genetic variants or loci that have been proven to be associated or conferring risk to T2DM or contribute to the individual differences in the susceptibility or predisposition to this disease. The identification of these variants has followed three main waves, from family-based linkage studies, while passing through candidate gene analysis, Genome Wide Association Study (GWAS) and then large-scale studies of association between certain DNA sequence variants in different ethnic groups [3], more than 60 susceptibility gene mutations for T2DM have been described. Their numbers started increasing in 2007 with the first GWAS which by replication in other populations in the world improved the capacity for researchers to discover positions and gene polymorphisms implicated in the susceptibility of metabolic disease phenotypes [4]- [9]. In Africa, only two GWAS conducted to date on the Africa America Diabetes Mellitus [10] [11]. Yako and collaborators showed that until June 2014 only, 100 polymorphisms including SNP, indels, and repeats in 57 genes were investigated, with the majority of studies carry out on the white populations from Northern African countries, principally Tunisia and Egypt. The genetic risk factors revealed by their meta-analysis represent the most promising T2DM risk genes identified and described to date in Africans [12].
Focused on these ten genes, TPMT (Thiopurine S- (Guanine nucleotide binding protein, beta polypeptide 1), MYL5 (Myosin, light chain 5, regulatory) with Trans associations driven by rs4731702 (C/T) polymorphism, the Krüppel Like Factor 14 (KLF14) gene (intronless member of the KLF family located at chromosome 7q32) [13] has been identified as a master switch gene and trans-regulatory to multiple metabolic phenotypes including T2DM [14]. This transcription factor family, of which 17 have been identified in mammalian systems, is characterized by three highly conserved (Cys2/His2-type) and homologous C-terminal zinc finger domains. These domains are implicated in regulation by DNA binding through the activation and/or repression of the transcription of many genes with roles in diverse biological processes that include responses to external stress, growth, proliferation, differentiation, development and survival due to their variable N-terminal domain [15] [16]. In addition to this exciting discovery, in a Cameroonian population, studies on the PPAR-γ2 Pro12Ala gene polymorphism [17] and the TCF7L2 rs12255372 (G/T), rs7903146 (C/T) gene polymorphisms [17] [18] showed that TCF7L2 rs7903146 gene polymorphism is strongly associated with T2DM, but contrary to other populations, the T allele was not associated with T2DM; it rather had a protective effect [19]. For these reasons, it is therefore important to study and understand the implication of the KLF14 rs4731702 (C/T) gene polymorphism in the predisposition to T2DM among Cameroonians. This will help to provide valuable insight on the genetic factors of T2DM, and thus contribute to the creation of a large database and the idea of personalized medicine.

Sample Preparation
Two venous blood samples were aseptically collected in EDTA and plain tubes in the morning following an overnight fasting for at least 12 hours. They were kept on ice (4˚C) and immediately transported to the laboratory where serum specimen was separated accordingly from the plain tube sample by centrifuging for 5 minutes at 3000 rpm. The extraction of genomic DNA was done from the dried blood stains on the Whatmann filter paper (from EDTA tube sample) by the Chelex method [24] and stored at −20˚C for further analysis.

Biochemical Assays
FPG levels were measured by the glucose oxidase-peroxidase method using an automatic portable Life Scan OneTouch Ultra glucometer (Johnson & Johnson, USA). Total cholesterol (TC) (cholesterol oxidase phenol-4-amino antipyrene peroxidase method, derived from that described by Allain and collaborators) [25], serum triglycerides (TG) (glycerol phosphatase oxidase-phenol4-amino antipyrene peroxidase method, derived from that described by Buccolo and Davids) [26], and high-density lipoprotein (HDL)-cholesterol (cholesterol oxidase phenol-4-amino antipyrene peroxidase method, in the supernatant, derived from that described by Burstein and collaborators) [27] were measured by standardized enzymatic methods on a spectrophotometer (UV Mini 1240) using Chronolab kits. The Friedwald formula was used to calculate Low-density lipoprotein (LDL)-cholesterol concentrations, when TG levels were below 4 mmol/L, and measured when TG values were over 4 mmol/L [28]. Dyslipidemia was considered as an elevated level of TC (>6.2 mmol/L) and/or an elevated level of Open Journal of Genetics LDL-cholesterol (>4.1 mmol/L) and/or a low HDL-cholesterol level (<1.04 mmol/L in men and 1.29 mmol/L in women) and/or an elevated level of TG (≥1.7 mmol/L) [29].

DNA Extraction, Amplification and Molecular Genotyping
Genomic DNA was extracted from filter paper stained with whole blood by the Chelex method. One hundred and eighty (180)

Sample Size Calculation
This was performed prior to the initiation of the study.

Data Management and Statistical Analyses
Participant data obtained were entered into a log book, and later keyed into a computer using the 2016 version of Microsoft excel sheets and verified for the possibility of entering errors. Genotype and allele distributions in patients with T2DM and healthy controls were obtained by direct counting. Qualitative variables were analyzed by the Chi square (χ 2 ) test or Fisher's exact test. Quantitative variables were compared using non-parametric tests (Mann Whitney or Kruskall Wallis with post hoc multiple comparison by Dunn-Sidak test) and described using median and inter quartile domain (IQR, 25th-75th percentiles) or mean ± standard deviation (M ± SD), and categorical variables using their frequency and percentage. The genotype frequencies were tested for the Hardy-Weinberg equilibrium using a χ 2 test. Odd Ratios (OR) with 95% confidence intervals (CI), were calculated using unconditional logistic regression. Data were coded, entered and analyzed using the Statistical Package for Social Sciences (SPSS) version 20.0 for Windows (Chicago, Illinois, USA) and were considered as statistically significant when p < 0.05.

Characteristics of the Study Population
The characteristics of the studied population are presented in

Frequency of KLF14 rs4731702 (C/T) Gene Polymorphism
All T2DM patients and normoglycemic controls were positively genotyped for the KLF14 rs4731702(C/T) gene polymorphism. After amplification characterized on agarose gel by one band of 347 bp (Figure 1), the genotyping was cha-

Correlation between Genetic Variants and Diabetic Traits
According to the rs4731702 (C/T) genotypes, the genotype-phenotype correla-    As for the KLF14 rs4731702 (C/T) gene polymorphism, no significant genotype-phenotype characteristics were observed in the control group and also in a specific phenotype of T2DM (data not shown).  and obesity. Their research suggested a trans-interaction between the expressions of the KLF14 gene and ten other genes implicated in a variety of metabolic disorders [14].

Discussion
Recently, Gao and co-workers conducted an investigation on the association of the KLF14 gene with another SNP (rs972283) and find no association with T2DM in Han Chinese population of the Henan province [34], this was the first study on this gene in association with T2DM. In this Cameroonian population, we conducted the second study on this gene but not with the same polymorphism. In our total study population, the distribution of the CC genotype was 46.11% (83/180), vs. 20.00% (36/180) and 33.89% (61/180) for the CT and the TT genotypes respectively, showing that this population was deviated from Hardy-Weinberg equilibrium (χ 2 = 34.76; P < 0.0001) in the general population, probably due to the high frequency of homozygotes in our study population or to the impact of the rapid increase of T2DM in Cameroonian population [2]. This deviation was most probably due to our sample size as described in: "Testing for Hardy-Weinberg equilibrium in small samples" by Elston and Forthofer [35].
This KLF14 rs4731702 (C/T) gene variant was not preferentially associated with a specific disease phenotype but was related to the CC, CT and TT genotypes. The stratification of clinical and biochemical parameters showed that the FPG median was significantly different (p < 0.0001) in the three (CC, CT and TT) genotype groups, with the higher values in the individuals presenting the CT genotype. The medians concentrations of TC (p < 0.0001), HDL-C (p = 0.0004) and LDL-C (p < 0.0001) were significantly different with the higher values in the individuals presenting the TT genotype. Interestingly, these two genotypes (CT and TT) were shown in this study to be associated with T2DM, compared to the CC genotype which was shown to have a protective effect in our population. This confirms that the T allele for genetic variant not only predisposes for T2DM but could be implicated in the metabolic disorders in the general population.

Conclusion
In conclusion, the present study showed that genotype and allele distributions of KLF14 rs4731702 (C/T) gene polymorphism are different between T2DM patients and healthy controls. It also showed for the first time that the KLF14 rs4731702 (C/T) gene polymorphism is strongly associated with an increased risk of T2DM in this Cameroonian population. In addition, this association is not dependent on a specific phenotype of disease. This candidate genetic variant is a promising target for personalized medicine for the populations of sub-Saharan Africa through the development of clinical genetic testing.

Ethics Approval and Informed Consent
The National Ethical Review Board of the Cameroon Ministry of Public Health provided an ethical clearance approving the study protocol. Signed informed consent was obtained from all participants after the procedures had been fully explained. The study was carried out according to the guidelines of the Helsinki Declaration.

Data Availability
All the data created and used to support the findings of this study are included within the article. However, any additional data, to support findings of this study, are available from the corresponding author upon request.