| Literature DB >> 35109885 |
Hamza Dallali1, Meriem Hechmi1,2, Imane Morjane3, Sahar Elouej1, Haifa Jmel1, Yosra Ben Halima1, Abdelmajid Abid1,4, Afef Bahlous5, Abdelhamid Barakat3, Henda Jamoussi1,4, Sonia Abdelhak1,6, Rym Kefi7,8.
Abstract
BACKGROUND: Variants in the Hepatocyte Nuclear Factor 1 Alpha gene (HNF1A) are associated with lipoproteins levels and type 2 diabetes. In this study, we aimed to assess the association of HNF1A gene and haplotypes with the metabolic syndrome (MetS) and its components through an association study in the Tunisian population as well as by a meta-analysis.Entities:
Keywords: Haplotype; Hepatocyte Nuclear Factor-1-Alpha gene; Lipids; Metabolic disorders; North Africa; SNP
Year: 2022 PMID: 35109885 PMCID: PMC8812021 DOI: 10.1186/s13098-022-00794-0
Source DB: PubMed Journal: Diabetol Metab Syndr ISSN: 1758-5996 Impact factor: 3.320
Clinical and biochemical characteristics of the studied Tunisian population
| Controls (n = 299) | Mets (n = 295) | p-value | |
|---|---|---|---|
| Age (years) | 52.56 ± 10.09 | 56.58 ± 8.56 | < 0.001 |
| WC (cm) | 97.07 ± 11.87 | 106.50 ± 9.94 | < 0.001 |
| BMI (Kg/m2) | 28.41 ± 4.83 | 31.53 ± 5.12 | < 0.001 |
| FPG (mmol/l) | 6.13 ± 2.51 | 9.52 ± 4.28 | < 0.001 |
| TC (mmol/l) | 5.08 ± 0.92 | 5.16 ± 1.01 | 0.28 |
| HDL (mmol/l) | 1.48 ± 0.41 | 1.13 ± 0.34 | < 0.001 |
| LDL (mmol/l) | 3.12 ± 0.89 | 3.16 ± 1.34 | 0.049 |
| TG (mmol/l) | 1.29 ± 0.56 | 2.02 ± 0.93 | < 0.001 |
| DBP (mmHg) | 7.74 ± 1.26 | 8.35 ± 1.40 | < 0.001 |
| SBP (mmHg) | 13.20 ± 1.97 | 14.6 ± 2.1 | < 0.001 |
BMI Body Mass Index, DBP diastolic blood pressure, FPG fasting plasma glucose, HDL high density lipoprotein cholesterol, LDL low density lipoprotein cholesterol, SBP systolic blood pressure, TC total cholesterol, TG triglycerides, WC waist circumference. Data are presented as mean ± standard deviation (SD)
Association of HNF1A variants with metabolic syndrome traits in the studied Tunisian population
| rs1169288 | rs2464196 | rs735396 | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AA + AC | CC | p-value | p-value* | GG + GA | AA | p-value | p-value* | TT + TC | CC | p-value | p-value* | |
| WC (cm) | 101.6 | 102.3 | 0.65 | 1 | 101.6 | 105.3 | 0.035a | 0.105 | 101.5 | 104.3 | 0.013a | 0.039a |
| BMI (kg/m2) | 30.05 | 30.17 | 0.99 | 1 | 29.93 | 30.68 | 0.1 | 0.3 | 29.94 | 30.35 | 0.35 | 1 |
| FPG (mmol/l) | 7.81 | 8.68 | 0.1 | 0.3 | 7.8 | 8.36 | 0.47 | 1 | 7.9 | 7.88 | 0.85 | 1 |
| SBP (mmHg) | 14.01 | 13.81 | 0.48 | 1 | 13.95 | 14.11 | 0.62 | 1 | 13.98 | 13.95 | 0.72 | 1 |
| DBP (mmHg) | 8.08 | 8.08 | 0.99 | 1 | 8.07 | 8.08 | 0.61 | 1 | 8.11 | 7.97 | 0.27 | 0.81 |
| TC (mmol/l) | 5.09 | 5.31 | 0.056 | 0.168 | 5.08 | 5.30 | 0.056 | 0.168 | 5.11 | 5.13 | 0.83 | 1 |
| HDL (mmol/l) | 1.30 | 1.38 | 0.07 | 0.21 | 1.3 | 1.37 | 0.037a | 0.111 | 1.29 | 1.36 | 0.08 | 0.24 |
| LDL (mmol/l) | 3.24 | 3.31 | 0.61 | 1 | 3.23 | 3.34 | 0.45 | 1 | 3.24 | 3.25 | 0.9 | 1 |
| TG (mmol/l) | 1.66 | 1.76 | 0.5 | 1 | 1.66 | 1.71 | 0.96 | 1 | 1.66 | 1.69 | 0.8 | 1 |
Data are presented as means. Linear regression, adjusted for age, sex and BMI, was used to assess genotype phenotype correlations under the recessive model of inheritance
BMI Body Mass Index, DBP diastolic blood pressure, FPG fasting plasma glucose, HDL high density lipoprotein cholesterol, LDL low density lipoprotein cholesterol, SBP systolic blood pressure, TC total cholesterol, TG Triglycerides, WC waist circumference
aIndicated a significant result
p-value*: p-values after Bonferroni correction
For the Bonferroni correction, p-values were multiplied by 3 (the number of SNPs in our study)
Calculations were performed using SNPassoc R package
Fig. 1Linkage disequilibrium (LD) plot for the three genotyped HNF1A polymorphisms in the Tunisian study sample. Each number in the squares refers to the r2 coefficient of LD between the correspondent SNPs multiplied by 100. The LD plot was generated using the Haploview software (version 4.2)
Characteristics of the studies included in the meta-analysis
| Study | Population | Group | Subjects | Average age (years) | rs1169288 | rs2464196 | rs735396 | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AA | AC | CC | GG | GA | AA | TT | TC | CC | |||||
| Morjane et al. (2017) | Morocco | Controls | 137 | 50.6 ± 10.34 | 82 | 38 | 10 | 53 | 57 | 25 | 39 | 70 | 26 |
| Cases | 104 | 57.59 ± 11.57 | 39 | 44 | 14 | 27 | 44 | 27 | 39 | 42 | 23 | ||
| Present study | Tunisia | Controls | 299 | 52.56 ± 10.09 | 116 | 136 | 44 | 107 | 141 | 51 | 79 | 140 | 79 |
| Cases | 295 | 56.4 ± 8.50 | 106 | 151 | 37 | 98 | 151 | 46 | 77 | 149 | 67 | ||
Results of meta-analysis using different genetic models
| SNP | Genetic model | Fixed effects model | Random effects model | Heterogeneity | |||
|---|---|---|---|---|---|---|---|
| OR (95% CI) | p-value | OR (95% CI) | p-value | P-value | I2 (%) | ||
| rs1169288 | AC vs AA | 1.27 (0.91–1.79) | 0.15 | 1.42 (0.68–2.95) | 0.33 | 0.047 | 74.47 |
| A > C | CC vs AA | 1.14 (0.68–1.90) | 0.61 | 1.36 (0.46–3.99) | 0.57 | 0.058 | 72.16 |
| AC + CC vs AA | 1.26 (0.91–1.73) | 0.14 | 1.43 (0.64–3.20) | 0.37 | 0.018 | 81.88 | |
| CC vs AC + AA | 1.01 (0.19–0.63) | 0.94 | 1.12 (0.52–2.41) | 0.76 | 0.149 | 51.76 | |
| rs2464196 | GA vs GG | 1.21 (0.85–1.71) | 0.28 | 1.28 (0.75–2.18) | 0.35 | 0.164 | 48.13 |
| G > A | AA vs GG | 1.19 (0.75–1.88) | 0.44 | 1.39 (0.42–4.55) | 0.57 | 0.013 | 83.45 |
| GA + AA vs GG | 1.19 (0.86–1.66) | 0.28 | 1.35 (0.65–2.82) | 0.41 | 0.042 | 75.65 | |
| AA vs GA + GG | 1.07 (0.71–1.61) | 0.73 | 1.16 (0.49–2.78) | 0.72 | 0.039 | 76.52 | |
| rs735396 | TC vs TT | 0.84 (0.58–1.21) | 0.35 | 0.82 (0.52–1.28) | 0.39 | 0.234 | 29.18 |
| T > C | CC vs TT | 0.81 (0.53–1.24) | 0.34 | 0.81 (0.53–1.24) | 0.34 | 0.958 | 0 |
| TC + CC vs TT | 0.83 (0.59–1.63) | 0.28 | 0.83 (0.59–1.16) | 0.28 | 0.389 | 0 | |
| CC vs TC + TT | 0.89 (0.61–1.67) | 0.53 | 0.89 (0.61–1.27) | 0.53 | 0.548 | 0 | |
OR Odds ratio, CI Confidence interval
Fig. 2Forest plots showing the meta-analysis results of the association between rs1169288 (A > C) and MetS in women. a Genetic model: AC vs AA, b Genetic model: CC vs AA, c Genetic model: AC + CC vs AA, d Genetic model: CC vs AA + AC. The forest plots were generated using “rmeta” R library