Association of TNF-α 308G/A and LEPR Gln223Arg Polymorphisms with the Risk of Type 2 Diabetes Mellitus
by
, , ,
Maria Trapali
1,†, 
Dimitra Houhoula
2,†,
Anthimia Batrinou
2,
Anastasia Kanellou
2,
Irini F. Strati
2,
Argyris Siatelis
3 and
Panagiotis Halvatsiotis
4,* 1
Department of Biomedical Medicine, University of West Attica, 12243 Attiki, Greece
2
Department of Food Science and Technology, University of West Attica, 12243 Attiki, Greece
3
3rd Department of Urologist Medical School, National and Kapodistrian University of Athens, “ATTIKON” University Hospital, 12462 Chaidari, Greece
4
2nd Propaedeutic Department of Internal Medicine, Medical School, National and Kapodistrian University of Athens, “ATTIKON” University Hospital, 12462 Chaidari, Greece
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Genes 2022, 13(1), 59; https://doi.org/10.3390/genes13010059
Submission received: 22 November 2021
/
Revised: 20 December 2021
/
Accepted: 21 December 2021
/
Published: 27 December 2021
(This article belongs to the Section Genetic Diagnosis)
Abstract
:The objective of the present study was to identify the association of the TNF-α- 308G/A and leptin receptor (LEPR) Gln223Arg polymorphisms with the risk of development of type 2 diabetes mellitus (T2DM). Methods: A total of 160 volunteers were studied: 108 with T2DM and 52 participants as control, who served as the control group. Polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) for the genomic region of TNF-α- 308G/A and LEPR Gln223Arg were carried out. Results: The frequency of LEPR Gln223Arg genotypes in T2DM and control groups showed significant differences in the distribution of genotypes (p < 0.05). The frequency also of TNF-α- 308G/A genotypes in T2DM and control subjects showed significant differences in the distribution of genotypes (p < 0.05). Conclusion: Our results indicate that there are significant differences in the distribution of genotypes and alleles between the individuals with T2DM and control subjects (p < 0.05).
1. Introduction
Type 2 diabetes mellitus (T2DM) is characterized as a disorder of impaired energy metabolism caused by insufficient insulin production and/or decreased insulin sensitivity. The etiology remains unclear but many environmental and polygenic factors may contribute to the development of T2DM. Although the pathogenesis of T2DM is still unclear, the increasing prevalence of the disorder is of great importance and a global public health concern. HbA1c is the gold standard for evaluating the long-term glycaemic control in diabetes, because it accurately reflects real glycaemic levels in vivo [1] The American Diabetes Association (ADA) treatment guidelines suggest an HbA1c level <7.0% as the primary glycaemic control target for people with diabetes, and the decrease in HbA1c level consequently reduces the prevalence of the devastating diabetes-related chronic complications [2].
Adipose tissue is a very active endocrine organ, secreting a number of hormones, such as adiponectin, leptin, resistin and visfatin, collectively with classical cytokines, such as tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6). All these adipocytokines play significant role in the regulation of energy metabolism, the metabolism of glucose and lipids, reproduction, cardiovascular function and immunity [3]. TNF-α plays a critical role in several autoimmune diseases, such as rheumatoid arthritis, and may mediate obesity-linked insulin resistance in type 2 diabetes. Upregulated expression of TNF-α plays a significant role in the induction of insulin resistance linked with obesity and T2DM [4]. Genetic variations in the promoter region of TNF-α may regulate transcription and production of the protein and may influence inflammatory diseases. Various studies have investigated single nucleotide polymorphisms (SNPs) in the promoter region of the human TNF gene, such as 238G/A, 308G/A, 857C/T and 1031T/C [5]. Two studies relate the studied polymorphism in gene 308G/A with T2DM and coronary heart disease, while in two other studies, their presence was related in people with type 2 diabetes, burdened with nephropathy. Nevertheless, there are studies that relate directly TNF gene polymorphism with T2DM development [6]. Chronic low-grade inflammation, which has been referred as “metaflammation”, is considered as a relevant factor contributing to the development of diabetic complications [7]. However, the association between the TNFα promoter genotypes and the risk of T2DM development remains controversial [8].
Leptin is an adipocytokine, considered as a crucial metabolic regulator with a primary role in reducing food intake, increasing energy expenditure and to regulating immune and inflammatory responses by binding and activating the leptin receptor [9,10]. Several studies relate leptin gene (LEP) and leptin receptor gene (LEPR) polymorphisms with obesity [11,12], insulin resistance [13] and T2DM [14]. The gene polymorphisms of LEP G2548A (rs7799039: guanine > adenine) and LEPR Gln223Arg (rs1137101: glutamine > arginine) have been examined extensively and significant associations of LEPR Gln223Arg polymorphism, where the circulating leptin and glucose levels were observed [15]. A mutation in the exon 6 of LEPR “rs1137101 (Gln223Arg)”, has been extensively studied. This specific polymorphism has been reported in several populations. It has an A to G transition, in which a codon CAG changes to CGG, resulting in the substitution of glutamine by arginine (Gln223Arg) in the LEPR. The location of this mutation is on the 6th exon of the gene and may impair signal transduction enough to increase susceptibility to T2DM. This study aimed to compare the two gene polymorphisms 308G/A (TNF-α) and Gln223Arg (LEPR) with the risk of T2DM development in a cohort of people with T2DM in the Greek population, for which limited data exist.
2. Materials and Methods
2.1. Collection of Clinical Samples
A total of 160 venous blood samples were collected from 108 volunteers (58 men and 50 women) with T2DM with a mean age of 67.5 ± 12.6 years old. A group of 52 volunteers (22 men and 30 women) without diabetes or other chronic diseases with a mean age of 51 ± 17.7 years old served as the control sample. Blood was collected in an EDTA containing vacutainer tube early in the morning and then transported in sterile tubes and stored immediately thereafter at −20 °C. Plasma glucose was measured using local laboratories with blood collected at the time of presentation to the hospital and the patients were not necessarily fasting prior to blood collection. All participants resided in the municipal area of Athens and the study period was from early June to late July 2021. All volunteers with GHbA1c > to 7.5% were considered as people with type 2 diabetes mellitus, while GHbA1c levels with normal fasting blood sugar levels and without any abnormal measurements in the past history were accepted as non-diabetic participants.
2.2. Questionnaire
We evaluated the demographics data (sex and age) and biochemical parameters (glucose, glucosylated heamoglobin).
2.3. Genomic DNA Extraction
DNA was extracted directly from blood specimens using an automatic extractor with the Whole Blood Nucleic Acid Extraction Kit (ZYBIO Company, Germany) following the protocol recommended by the supplier. The purity and the quantity of extracted DNA were evaluated spectrophotometrically by calculating OD260/OD280 (spectrophotometer Epoch, Biotek, Winusky, VT, USA).
2.4. Polymerase Chain Reaction–Restricted Fragment Length Polymorphism (PCR-RFLP) for the Genomic Region of TNF-α -308G/A
After checking for the purity of DNA, PCR was carried out. The chosen primers amplify a size of 107 bp the genomic region of TNF-α- 308G/A single nucleotide polymorphism in the promoter region of TNF using 0.3 μL of primers forward 5′-AGGCAATAGGTTTTGAGGGCCAT-3′ and reverse 5′-TCCTCCCTGCTCCGATTCCG-3′. PCR was performed in 50 μL final volume solution using the Master Mix (PCRBIO TaqMix Red, PCRBIOSYSTEMS, London, UK). The amplification was conducted by a thermal cycler (96-well thermal cycler Applied Biosystems, Waltham, MA, USA), as follows: an initial denaturation: 95 °C, 3 min; 40 cycles with the following step-cycle profile: denaturation 95 °C, 15 s; annealing 60 °C, 15 s; extension 72 °C, 60 s; final extension 72 °C, 10 min.
PCR products were separated in 2% agarose gel, stained with ethidium bromide (0.5 μg/mL) and documented under UV illumination using MiniBIS Pro device (DNR Bio-Imaging Systems Ltd., Neve Yamin, Israel).
The 107 bp PCR product was digested with NcoI (New England Biolabs, London, UK) restriction enzyme for 15 min at 37 °C. Three types of bands were observed—a complete NcoI cut representing homozygous TNF-α (-308G/G), resulting in two fragments of 87 and 20 bp; a partial cut representing heterozygous TNF-α (-308G/A), resulting in three fragments of 107, 87 and 20 bp; and an uncut 107 bp fragment representing homozygous TNF-α (-308A/A).
2.5. Polymerase Chain Reaction–Restricted Fragment Length Polymorphism (PCR-RFLP) for the Genomic Region of LEPR Gln223Arg
After checking for the purity of DNA, PCR was carried out. The chosen primers amplify a size of 421 bp the genomic region of LEPR Gln223Arg using 0.3 μL of the following primers: forward primer—5′-ACCCTTTAAGCTGGGTGTCCCAAATAG-3′; reverse primer—5′-AGCTAGCAAATATTTTTGTAAGCAATT-3′. PCR was performed in 50 μL final volume solution using Master Mix (PCRBIO TaqMix Red). The program of the PCR was as follows: an initial denaturation: 95 °C, 3 min; 40 cycles with the following step-cycle profile: denaturation 95 °C, 15 s; annealing 60 °C, 15 s; extension 72 °C, 60 s; final extension 72 °C, 10 min. PCR products were separated in 2% agarose gel, stained with ethidium bromide (0.5 μg/mL) and documented under UV illumination using a MiniBIS Pro device (DNR Bio-Imaging Systems Ltd., Neve Yamin, Israel).
The 421 bp PCR product was digested with MspI (Thermo Scientific, Waltham, MA, USA) restriction enzyme for 16 h at 65 °C. Three types of bands were observed—a complete MspI cut representing homozygous LEPR Gln223Arg (Arg/Arg), resulting in two fragments of 294 and 127 bp; a partial cut representing heterozygous Gln/Arg (421, 294 and 127 bp), resulting in three fragments of 421, 294 and 127 bp; and an uncut 421 bp fragment representing homozygous Gln/Gln (Figure 1).
2.6. Biomedical Ethics Issues
Institutional ethical approval was received prior to the study, and the collection of all epidemiological data were conducted in such a way as to fully guarantee and preserve anonymity and confidentiality. All the questionnaires were collected with the consent of the volunteers.
2.7. Statistical Analysis
The null hypothesis is accepted, since p > 0.05. The p value can be calculated in Excel (Microsoft, Redmond, Wash) with the formula chi-square distribution (CHISQ.DIST, X; df; T), where X is the value of the χ2-test, df is degrees of freedom and T(RUE) corresponds to the cumulative χ2 distribution. To find the correct value at the χ2 distribution table, we need the degrees of freedom, which are calculated by the following formula: df = (r − 1) × (c − 1), where c is the number of columns and r is the number of rows in our 2 × 2 table. The df = (2 − 1) × (2 − 1) = 1. The allele frequency among all participants is in accordance to the Hardy–Weinberg equilibrium. Multinomial logistic regression analysis was performed by SPSS software (Version 26).
3. Results
Overall, 50% of the volunteers were male and 50% were female. Out of these 160 participants, 67.5% (n = 108) had T2DM. The median glucose on blood collection time was 150 mg/dL for people with T2DM, while in 5.6% (n = 6) of them, a glucose level of ≥ 200 mg/dL was recorded. A glucose level < 85 mg/dL characterized all participants of the control group. All volunteers with diabetes presented with HbA1c > 7.0%.
Genotyping of the LEPR Gln223Arg and the genomic region of TNF-α -308G/A was assessed in the 52 controls and 108 T2DM participants. The frequency of LEPR Gln223Arg genotypes in T2DM and control groups is shown in Table 1, with significant differences in the distribution of genotypes (p < 0.05).
Individuals with diabetes who were homozygous on the A and G alleles were 42.6% and 13%, respectively, while heterozygous were 44.4%. The control group, which was homozygous on the G and A allele, was 7.7 and 65.4%, respectively. Statistically significant differences were also detected between the different groups (p < 0.05). In contrast, heterozygotes in the control group accounted only for 26.9%. All T2DM volunteers who were homozygous on allele A had plasma glucose levels between 124–304 mg/dL.
As for the Gln223Arg polymorphism (G-A), allele G occurs with a frequency of 35.2% in T2DM and 21.2% in controls. The A allele occurs with a frequency of 64.8% in T2DM and 78.8% in the control group (Table 2).
Genotyping of the TNF-α -308G/A was assessed in 52 control subjects and 108 T2DM volunteers. The frequency of TNF-α -308G/A genotypes in T2DM and control subjects are shown in Table 3, with significant differences in the distribution of genotypes (p < 0.05). People with diabetes who were homozygous on the A and G alleles were 0% and 68.5%, respectively, while T2DM subjects who were heterozygous were 31.5%. In the control group homozygous in G was the 57.7% while none (0%) was homozygous for the A allele. In contrast, heterozygotes in the control group accounted for 42.5%.
For the TNF-α -308G/A polymorphism the (G-A) form, it was shown that allele A occurs with a frequency of 15.7% in T2DM and 24% in controls. The G allele occurs with a frequency of 84.3% in T2DM and 76% in the control group (Table 4). Finally, all the 13 T2DM who were homozygous in the G allele, for the LEPRGln223Arg polymorphism, were homozygous on the G allele of the TNF-α -308G/A polymorphism. Table 5 presents the frequency of genotypes for both polymorphisms studied among genders, revealing non statistically significant differences (p > 0.05) in the T2DM group between the two genders except for the GA genotype of LEPR Gln223Arg.
Multinomial logistic regression analysis was performed for the LEPR and TNF-a genotypes and the results are presented in Table 6, Table 7, Table 8, Table 9, Table 10 and Table 11, respectively. The independent variables chosen were the following: gender (two categories: male, female), age group (three categories: 0–45, 46–65, >65) and T2DM group (two categories: diabetic, normal or control).
In Table 6, from “Model Fitting Information”, it is observed that the full model statistically significantly (p = 0.001) predicts the dependent variable (LEPR genotypes) better than the intercept-only model alone. In Table 7, “Likelihood Ratio Tests” present the independent variables that are statistically significant (i.e., age group variable and T2DM group variable with p = 0.006 and p = 0.000, respectively). In Table 8, “Parameter Estimates”, the first set of coefficients represents comparisons between AA and GG genotypes. “Age group >65” and “T2DM Diabetic group” were significant predictors: (b = 1.618, s.e. = 0.692, p = 0.019) and (b = −2.343, s.e. = 0.787, p = 0.003), respectively. Individuals scoring higher on the variable “T2DM Diabetic group” were less likely to have AA genotype. The odds ratio of 0.096 indicates that for every one unit increase on “T2DM Diabetic group” the odds of an individual having AA genotype changed by a factor of 0.096 (in other words, the odds were decreasing). The second and final set of coefficients represents comparisons between GA and GG genotypes. “Age group 0–45” and “T2DM Diabetic group” were negative predictors, although the specific parameters were not significant to the model.
In Table 9, from “Model Fitting Information”, it is observed that the model was not statistically significantly improved (p = 0.220), compared to the intercept-only model alone. “Likelihood Ratio Tests” (Table 10) showed that none of the independent variables (gender, age group and T2DM group) are statistically significant (p > 0.05). In Table 11, “Parameter Estimates”, the coefficients represent comparisons between GA and GG genotypes. More specifically, “age group >65”, “age group 0–45” and “T2DM Diabetic group” were negative predictors, although the specific parameters were not significant (p > 0.05) to the model.
4. Discussion
In our study, we reported an association between the leptin receptor gene Q223R polymorphism and the TNF-α -308G/A in a sample of T2DM volunteers. T2DM is considered a disease caused by a combination of genes and this polygenic nature has been linked to obesity, hypertension, gout, and disordered lipid metabolism. Leptin is a hormone derived from fat that may play a role in regulating metabolism of energy and body lipid homeostasis. The receptor of this hormone, the LEPR, belongs to the superfamily of cytokine receptors and is a single transmembrane protein with many spliced isoforms (one long isoform and several short isoforms) distributed in several tissues. The long isoform of LEPR is biologically active and abundantly expressed in the hypothalamus, where it activates the Janus kinase signal transducer and the activation of transcription (STAT) system resulting in alterations of transcription or translation of hypothalamic neuropeptides. Single nucleotide mutations (SNP’s) of the leptin receptor (LEPR) gene that result in a premature termination of the intracellular domain of the protein have been considered responsible for obesity. In particular, the Q223R polymorphisms (glutamine to arginine at codon 223) result in substitutions of amino acids in the extracellular region of the LEPR that may have potential functional consequences [12,15]. In the current analysis, a significant association between the LEPR Gln223Arg gene polymorphism and T2DM in the sample population was observed. Our analyses also revealed significant associations between TNF-α -308G/A and T2DM. Tumor necrosis factor-α (TNF-α) is a cytokine that has been found to play a role in insulin resistance and the TNF-α gene is one of the candidate genes implicated in type 2 diabetes mellitus (T2DM).
Our findings are in line with some studies regarding LEPR Gln223Arg expression [16], whereas they are contradictory to others; for example, [17,18] concluded that LEPR Gln223Arg gene polymorphism had no effect on the susceptibility to T2DM and did not consider any differences in regard of race and ethnicity. However, studies that examine different ethnic groups may yield conflicting results. LEPR Gln223Arg gene polymorphism has been associated with an increased risk of T2DM and thus, carriers of the G allele of LEPR Gln223Arg gene polymorphism may be more susceptible to T2DM than non-carriers of the G allele. However, our study is in agreement with a meta-analysis conducted in 2016 that has examined 11 studies (~5000 cases in total) and has concluded that the rs1137101(G) allele is associated significantly with T2DM, with an odds ratio of about 1.2–1.8 [19,20,21].
Based on the literature, it is inconclusive whether the -308G/A polymorphisms in the TNF-α promoter results in T2DM susceptibility [22,23,24,25,26]. However, our findings follow recent meta-analysis studies [27,28], suggesting that TNF-α -308G/A can be considered as a risk factor for T2DM.
A leading factor that may contribute to the development of T2DM is the composition of nutrients that an individual consumes, such as carbohydrates, fats, proteins, minerals and vitamins, which play a vital role in metabolic homeostasis. [29]. Additionally, gut microbiota alterations have been found not only in obesity but in multiple pathologies, ranging from intestinal bowel syndrome (IBS) and type 2 diabetes (T2D) [30]. Intervention studies are needed to explore the role of applied nutrigenetic and precision nutrition to counteract T2DM [31]. In this context, precision nutrition with customized dietary recommendations may be applied to an individual, in order to prevent and manage chronic diseases. Moreover, data suggest that the methylation levels of LEPR and the promoter of TNF-α could be used as epigenetic biomarkers to respond to a low-calorie diet. In addition, the methylation profile of the promoters of these genes could help predict susceptibility to comorbidities, such as hypertension or type 2 diabetes [32]. Future larger studies should be considered necessary, investigating different age groups as well. Therefore, while the main objective of our study was to investigate certain polymorphisms, we could not reproduce our conclusions for the complete genome variations of the studied biomarkers. In the future, it could be possible to schedule personalized nutritional strategies, with corrective dietary actions for the particular negative SNP carriers (LEPR Gln223Arg and TNF-α -308G/A). These solutions, eventually, may contribute to a better management of T2DM.
5. Conclusions
Our study concludes that the G allele in the LEPR Gln223Arg and TNF-α -308G/A polymorphisms has a significant higher frequency in T2DM. However, the limitation of our study is that the sample size is small and we are lacking an evaluation of an extensive number of possibly significant demographic and biochemical factors, that may play a role in the plasma LEPR and TNF levels. More research is therefore required to verify our conclusion.
Author Contributions
Conceptualization, D.H.; methodology, M.T., D.H. and P.H.; software, I.F.S.; validation, A.B. and I.F.S.; formal analysis, A.B., I.F.S., A.S. and A.K.; resources, D.H., A.B., M.T. and A.K.; data curation, P.H. and A.S.; writing—original draft preparation, D.H., M.T., A.B., I.F.S., P.H., A.K. and A.S.; writing—review and editing, D.H., A.B., P.H., A.K. and I.F.S.; supervision, D.H. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of General ATTIKO Hospital, Athens Greece (protocol code 453/26/08/21 and date of approval 7/09/21).
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Conflicts of Interest
The authors declare no conflict of interest.
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Figure 1.
Heterozygous G/A samples are represented in lanes 2, 6 and 11, in which the TNF-α promoter gene was partially cut with the MspI, resulting in 3 DNA fragments of 440, 300 and 140 bp, respectively. Homozygous A/A samples are represented by lanes 3–5 and 7–10 in which an uncut 440 bp fragment is observed. Lane 1 is a negative control and Lane 12, the DNA Ladder, is 100 bp.
Figure 1.
Heterozygous G/A samples are represented in lanes 2, 6 and 11, in which the TNF-α promoter gene was partially cut with the MspI, resulting in 3 DNA fragments of 440, 300 and 140 bp, respectively. Homozygous A/A samples are represented by lanes 3–5 and 7–10 in which an uncut 440 bp fragment is observed. Lane 1 is a negative control and Lane 12, the DNA Ladder, is 100 bp.
Table 1.
Frequency of LEPR Gln223Arg genotypes in T2DM and control groups.
| LEPR Gln223Arg | T2DM | Control |
|---|---|---|
| Gln/Gln (AA) | 46 (42.6%) a | 34 (65.4%) b |
| Gln/Arg (AG) | 48 (44.4%) a | 14 (26.9%) c |
| Arg/Arg (GG) | 14 (13%) b | 4 (7.7%) a |
Notes: a,b,c—different superscript letters in the same column or row indicate statistically significant differences (p < 0.05).
Table 2.
Frequency of LEPR Gln223Arg alleles in T2DM and control groups.
| LEPR Gln223Arg | T2DM | Control |
|---|---|---|
| G | 35.2% a | 21.2% b |
| A | 64.8% b | 78.8% a |
Notes: a,b—different superscript letters in the same column or row indicate statistically significant differences (p < 0.05).
Table 3.
Frequency of TNF-α -308G/A genotypes in T2DM and control subjects.
| TNF-α -308G/A | T2DM | Control |
|---|---|---|
| G/G | 74 (68.5%) a | 27 (51.9%) b |
| G/A | 34 (31.5%) c | 25 (48.1%) b |
Notes: a,b,c—different superscript letters in the same column or row indicate statistically significant differences (p < 0.05).
Table 4.
Frequency of TNF-α -308G/A alleles in T2DM and control groups.
| TNF-α -308G/A | T2DM | Control |
|---|---|---|
| G | 84.3% a | 76% b |
| A | 15.7% b | 24.0% a |
Notes: a,b Different superscript letters in the same column or row indicate statistically significant differences (p < 0.05).
Table 5.
Frequency of TNF-α -308G/A and LEPR Gln223Arg genotypes in T2DM and control subjects.
| Gender | TNF-α -308G/A (GA) | TNF-α -308G/A (GG) | LEPR Gln223Arg GG | LEPR Gln223Arg GA | LEPR Gln223Arg AA |
|---|---|---|---|---|---|
| Female (Control Group) | 17 (56.7%) a | 13 (43.3%) a | 3 (10%) a | 8 (26.7%) b | 19 (63.3%) c |
| Male (Control Group) | 8 (36.4%) b | 14(63.6%) c | 1 (4.5%) a | 6 (27.3%) b | 15 (68.2%) c |
| Female T2DM | 17(34%) b | 33 (66%) c | 4 (8%) a | 28 (56%) c | 18 (36%) b |
| Male T2DM | 17 (29.3%) b | 41(70.7%) c | 10 (17.2%) a | 20 (34.5%) b | 28 (48.3%) b |
Notes: a,b,c—different superscript letters in the same column or row (for each polymorphism) indicate statistically significant differences (p < 0.05).
Table 6.
Multinomial logistic regression analysis for the LEPR Gln223Arg genotypes. Model Fitting Information.
Table 6.
Multinomial logistic regression analysis for the LEPR Gln223Arg genotypes. Model Fitting Information.
| Model | Model Fitting Criteria | Likelihood Ratio Tests | ||
|---|---|---|---|---|
| −2 Log Likelihood | Chi-Square | df | Sig. | |
| Intercept Only | 85.541 | |||
| Final | 60.156 | 25.385 | 8 | 0.001 |
Sig. stands for “significance probability”.
Table 7.
Multinomial logistic regression analysis for the LEPR Gln223Arg genotypes. Likelihood Ratio Tests.
Table 7.
Multinomial logistic regression analysis for the LEPR Gln223Arg genotypes. Likelihood Ratio Tests.
| Effect | Model Fitting Criteria | Likelihood Ratio Tests | ||
|---|---|---|---|---|
| −2 Log Likelihood of Reduced Model | Chi-Square | df | Sig. | |
| Intercept | 60.156 a | 0.000 | 0 | |
| gender | 64.007 | 3.851 | 2 | 0.146 |
| agegroup | 74.445 | 14.289 | 4 | 0.006 |
| T2DM | 76.766 | 16.610 | 2 | 0.000 |
The chi-square statistic is the difference in −2 log-likelihoods between the final model and a reduced model. The reduced model is formed by omitting an effect from the final model. The null hypothesis is that all parameters of that effect are 0. a This reduced model is equivalent to the final model because omitting the effect does not increase the degrees of freedom. Sig. stands for “significance probability”.
Table 8.
Multinomial logistic regression analysis for the LEPR Gln223Arg genotypes. Parameter Estimates.
Table 8.
Multinomial logistic regression analysis for the LEPR Gln223Arg genotypes. Parameter Estimates.
| LEPRa | B | Std. Error | Wald | df | Sig. | Exp(B) | 95% Confidence Interval for Exp(B) | ||
|---|---|---|---|---|---|---|---|---|---|
| Lower Bound | Upper Bound | ||||||||
| AA | Intercept | 2.756 | 0.808 | 11.650 | 1 | 0.001 | |||
| [gender = FEMALE] | 0.263 | 0.575 | 0.209 | 1 | 0.648 | 1.300 | 0.421 | 4.013 | |
| [gender = MALE] | 0 b | . | . | 0 | . | . | . | . | |
| [agegroup = >65] | 1.618 | 0.692 | 5.465 | 1 | 0.019 | 5.043 | 1.299 | 19.580 | |
| [agegroup = 0–45] | −1.535 | 0.790 | 3.774 | 1 | 0.052 | 0.215 | 0.046 | 1.014 | |
| [agegroup = 45–65] | 0 b | . | . | 0 | . | . | . | . | |
| [T2DM = DIABETIC] | −2.343 | 0.787 | 8.853 | 1 | 0.003 | 0.096 | 0.021 | 0.449 | |
| [T2DM = NORMAL] | 0 b | . | . | 0 | . | . | . | . | |
| GA | Intercept | 1.382 | 0.827 | 2.791 | 1 | 0.095 | |||
| [gender = FEMALE] | 0.853 | 0.574 | 2.211 | 1 | 0.137 | 2.347 | 0.762 | 7.222 | |
| [gender = MALE] | 0 b | . | . | 0 | . | . | . | . | |
| [agegroup = >65] | 1.015 | 0.686 | 2.188 | 1 | 0.139 | 2.760 | 0.719 | 10.590 | |
| [agegroup = 0–45] | −1.072 | 0.767 | 1.955 | 1 | 0.162 | 0.342 | 0.076 | 1.538 | |
| [agegroup = 45–65] | 0 b | . | . | 0 | . | . | . | . | |
| [T2DM = DIABETIC] | −0.832 | 0.781 | 1.135 | 1 | 0.287 | 0.435 | 0.094 | 2.011 | |
| [T2DM = NORMAL] | 0 b | . | . | 0 | . | . | . | . | |
a The reference category is: GG. b This parameter is set to zero because it is redundant. Sig. stands for “significance probability”. Std. Error: Standard Error.
Table 9.
Multinomial logistic regression analysis for the TNF-a -308G/A genotypes. Model Fitting Information.
Table 9.
Multinomial logistic regression analysis for the TNF-a -308G/A genotypes. Model Fitting Information.
| Model | Model Fitting Criteria | Likelihood Ratio Tests | ||
|---|---|---|---|---|
| −2 Log Likelihood | Chi-Square | df | Sig. | |
| Intercept Only | 42.626 | |||
| Final | 36.887 | 5.739 | 4 | 0.220 |
Table 10.
Multinomial logistic regression analysis for the TNF-a -308G/A genotypes. Likelihood Ratio Tests.
Table 10.
Multinomial logistic regression analysis for the TNF-a -308G/A genotypes. Likelihood Ratio Tests.
| Effect | Model Fitting Criteria | Likelihood Ratio Tests | ||
|---|---|---|---|---|
| −2 Log Likelihood of Reduced Model | Chi-Square | df | Sig. | |
| Intercept | 36.887 a | 0.000 | 0 | . |
| gender | 38.162 | 1.275 | 1 | 0.259 |
| agegroup | 39.169 | 2.283 | 2 | 0.319 |
| T2DM | 39.962 | 3.075 | 1 | 0.080 |
The chi-square statistic is the difference in −2 log-likelihoods between the final model and a reduced model. The reduced model is formed by omitting an effect from the final model. The null hypothesis is that all parameters of that effect are 0. a This reduced model is equivalent to the final model because omitting the effect does not increase the degrees of freedom.
Table 11.
Multinomial logistic regression analysis for the TNF-a -308G/A genotypes. Parameter Estimates.
Table 11.
Multinomial logistic regression analysis for the TNF-a -308G/A genotypes. Parameter Estimates.
| TNFa | B | Std. Error | Wald | df | Sig. | Exp(B) | 95% Confidence Interval for Exp(B) | ||
|---|---|---|---|---|---|---|---|---|---|
| Lower Bound | Upper Bound | ||||||||
| GA | Intercept | −0.124 | 0.403 | 0.094 | 1 | 0.759 | |||
| [gender = FEMALE] | 0.383 | 0.340 | 1.268 | 1 | 0.260 | 1.466 | 0.753 | 2.855 | |
| [gender = MALE] | 0 b | . | . | 0 | . | . | . | . | |
| [agegroup = >65] | −0.112 | 0.392 | 0.082 | 1 | 0.775 | 0.894 | 0.414 | 1.928 | |
| [agegroup = 0–45] | −0.764 | 0.519 | 2.173 | 1 | 0.140 | 0.466 | 0.168 | 1.286 | |
| [agegroup = 45–65] | 0 b | . | . | 0 | . | . | . | . | |
| [T2DM = DIABETIC] | −0.726 | 0.417 | 3.032 | 1 | 0.082 | 0.484 | 0.214 | 1.095 | |
| [T2DM = NORMAL] | 0 b | . | . | 0 | . | . | . | . | |
a The reference category is: GG. b This parameter is set to zero because it is redundant.
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Trapali, M.; Houhoula, D.; Batrinou, A.; Kanellou, A.; Strati, I.F.; Siatelis, A.; Halvatsiotis, P. Association of TNF-α 308G/A and LEPR Gln223Arg Polymorphisms with the Risk of Type 2 Diabetes Mellitus. Genes 2022, 13, 59. https://doi.org/10.3390/genes13010059
AMA Style
Trapali M, Houhoula D, Batrinou A, Kanellou A, Strati IF, Siatelis A, Halvatsiotis P. Association of TNF-α 308G/A and LEPR Gln223Arg Polymorphisms with the Risk of Type 2 Diabetes Mellitus. Genes. 2022; 13(1):59. https://doi.org/10.3390/genes13010059
Chicago/Turabian StyleTrapali, Maria, Dimitra Houhoula, Anthimia Batrinou, Anastasia Kanellou, Irini F. Strati, Argyris Siatelis, and Panagiotis Halvatsiotis. 2022. "Association of TNF-α 308G/A and LEPR Gln223Arg Polymorphisms with the Risk of Type 2 Diabetes Mellitus" Genes 13, no. 1: 59. https://doi.org/10.3390/genes13010059
APA StyleTrapali, M., Houhoula, D., Batrinou, A., Kanellou, A., Strati, I. F., Siatelis, A., & Halvatsiotis, P. (2022). Association of TNF-α 308G/A and LEPR Gln223Arg Polymorphisms with the Risk of Type 2 Diabetes Mellitus. Genes, 13(1), 59. https://doi.org/10.3390/genes13010059
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