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Research Article - (2021) Volume 7, Issue 3

Investigatıon of BDNF and TAQI Gene Polymorphısms in Patients wıth Breast Cancer with Metabolic Syndrome

Ketenci Sema1, Demirkol Şeyda2, Sönmez Dilara3, Giray Özlem4, Aydın Armagan5, Kepenek Ata6, Karapirli Kübra6, Geyikoglu İpek6, Arda Sena6, Berk C. Selim6, Baghaki Sema7, Demircan Günnur8, Yaylım İlhan3 and Akın Demet9

1Faculty of Medicine, İstanbul Atlas University, Turkey

2Faculty of Engineering and Natural Sciences, Biruni University, Istanbul,Turkey

3Department of Molecular Medicine, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Turkey

4Department of Pharmacology, SBU Antalya Training And Research Hospital, Turkey

5Department of Oncology, SBU Antalya Training And Research Hospital, Turkey

6Department of Medicine, Bahcesehir University, Turkey

7Department of Obstetrics and Gynecology, Bakirkoy Dr. Sadi Konuk Training and Research Hospital, University of Health Sciences, Turkey

8Faculty of Medicine, Medical Biology and Genetic, Demiroglu Bilim University, Turkey

9Bahcesehir University, Faculty of Medicine, Medical Pharmacology, Turkey

Corresponding Author:
Ketenci Sema
Faculty of Medicine
İstanbul Atlas University, Turkey
Tel: 5418344034

Received Date: October 06, 2021; Accepted Date: February 22, 2021; Published Date: March 01, 2021

Citation: Sema K, Şeyda D, Dilara S, Özlem G, Armagan A, et al. (2021) Investigatıon of BDNF and TAQI Gene Polymorphısms in Patients wıth Breast Cancer with Metabolic Syndrome. Biochem Mol Biol Vol.7 No.3:11.

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Many studies have shown that BDNF and TaqI can play a role in metabolic pathogenesis. This study aims to investigate the possible relationship between BDNF and TaqI gene polymorphisms, susceptibility to metabolic disease and psychopathological symptoms in female breast cancer patients. The potential pathophysiological relationship between metabolic syndrome (MetS) and breast cancer can be affected by the hormonal status of the cancer. For MetS, it is clinically important to determine the potential effects of different diagnostic criteria created by the hormone receptors (HR) status on the results of the metaanalysis. This large-scale prospective study was analyzed as a case-control study to determine the relationship between MetS and clinical outcomes in women with breast cancer, with 80 patients and 45 controls enrolled only in women. There was no significant difference in the genotype and allele distributions of polymorphism of both genes between the patient and control groups, but trends that made significant overall differences in metabolic pathogenesis were observed in the controls of patients with breast cancer. The findings suggest that the effects of gene polymorphisms on metabolic pathogenesis may be a pioneer in detecting negative symptoms in breast cancer diagnosis. As we know, metabolic pathway gene variations have been shown to be important in the development process of metabolic diseases. Many studies have shown that BDNF and TaqI gene polymorphisms are important in breast cancer. Recently, genetically related studies with cancer-targeting SNPs have focused on determining susceptibility, survival, complications, or responses to pharmacological intervention. The aim of our study is to investigate the possible relationship between susceptibility to metabolic disease and psychopathological symptoms.


BDNF; TaqI; Breast cancer; Metabolic sendrome (MetS); Polymorphism


Despite advances in cancer prevention and management around the world, breast cancer continues to be a common malignancy in women, and it is known that approximately 1.4 million women are diagnosed with breast cancer annually [1]. However, due to the delays in analysis and diagnosis every day, it can develop uncontrolled and spread to other parts of the body with non-invasive and invasive forms. Breast cancer is generally considered to be a multifactorial disease in which estrogens are one of the main factors [2]. The risk of breast cancer associated with separate genotypes of each of a set of genes that interact as enzymes in estrogen metabolism in breast tissue has been studied in several studies, but the results were inconsistent and conflicting as determining a woman's genotype adds another dimension to the assessment of overall breast cancer risk [3,4]. However, there is also interaction between genotype risk factors and traditional hormonal risk factors (For example, obesity has been associated with both endogenous estrogen concentration and breast cancer risk. Several studies have shown that obese postmenopausal women have a higher risk for breast cancer compared to age-appropriate postmenopausal women who are not obese) have been demonstrated in other studies [5,6]. Metabolic diseases; These are pathological pictures that develop as a result of disorders related to the synthesis or degradation of proteins, carbohydrates and fatty acids. Although nearly 700 metabolic diseases have been defined so far, pathology in metabolic disorders occurs due to the absence or insufficiency of the enzyme that cannot be formed or cannot perform its function due to faulty genetic information. The synthesis of enzymes and proteins that function in biochemical pathways is encoded by genes on different chromosomes. Mutations that occur in genes can cause enzyme synthesis, decrease in activity or impairment of enzyme binding and activation of cofactor. Mutations can affect enzymes as well as impair the amount or functions of carrier proteins. Hereditary metabolic diseases (CMD) can present with very different clinical findings that concern all systems. Even patients with the same metabolic disease may have very different clinical findings. These differences in clinical findings arise from the fact that the amount and functions of enzymes, cofactors or carrier proteins can be affected to varying degrees due to the variety of mutations in that gene. Especially in hereditary metabolic diseases, the contribution of clinical laboratory tests to clinical decision-making and treatment guidance is very high. Metabolic diseases are often inherited, but most people affected by them can appear healthy for days, months or even years. The onset of symptoms usually occurs when the body's metabolism is under stress. The history of metabolic diseases (such as occurrence, crises, symptoms, aversion to food) is also related to the proper functioning of the endocrine system and the strong or weak panetric distribution. The majority of these are caused by single gene errors that encode enzymes that facilitate the conversion of one substance to another. Metabolic syndrome (MetS) has been suggested to be a risk factor for many cancers, including breast cancer. However, it remains unclear whether MetS predicts a poor prognosis in women with breast cancer. In a meta-analysis to summarize the relationship between MetS and clinical outcome in women with breast cancer, it has been shown that MetS is significantly associated with an increased risk of breast cancer recurrence [7]. MetS has been suggested as a prognostic factor in women with breast cancer. In particular, MetS has been associated with the more aggressive tumor biology of breast cancer [8,9]. These results show that MetS may be a prognostic factor and predict a higher overall risk of death in women with breast cancer [7]. One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes to common complex multifactorial human diseases. This difficulty is partly due to the limitations of parametric-statistical methods for detecting gene effects that are solely or partially due to interactions with other genes and environmental exposures [2]. The role of specific alleles of the genetic (BDNF and TaqI) genes that play a role in the complex etiology of breast cancer needs to be further investigated, as they may determine an increased risk for breast cancer.

The brain-derived neurotrophic factor BDNF gene is approximately 70kb in length on the short arm (p) of chromosome 11 (11p14.1). This gene encodes pro BDNF, a progenitor peptide that proteolytically turns into general. Single nucleotide polymorphisms (SNPs) of the gene encoding the BDNF protein are frequently encountered [10]. These include the single nucleotide polymorphism (SNP) at nucleotide 196G/A resulting in an amino acid substitution (Val to Methionine) at the 66th codon of the proBDNF molecule (Val-66Met) [11]. At the same time, the genetic brain-derived neurotrophic factor (BDNF) Val-66 Met polymorphism, which has been extensively studied for the formation of social perception and its role in affecting empathy, has been identified as a potential target in neuroimaging studies based on its effect on emotional perception and social perception and is associated with the amygdala [12,13]. Preliminary data hypothesize that the reduction of a single nucleotide polymorphism (rs6265) of the BDNF gene may predispose patients to cognitive impairment [13]. The TaqI gene is a DNAtype transposon. Thus, Taql is mobile and has the potential to generate splice mutations useful for gene tagging [14]. TaqI is an important gene for the isolation and characterization of endonuclease mutants [15] and plays an important role in neuronal migration by exhibiting binary genetic interactions. In addition, Taq1 encodes cell-cell or cell-matrix interactions that are transiently expressed in various neurons and can regulate cell-cell or cell-matrix interactions, and can regulate cell-cell or cell-matrix interactions that affect intracellular signaling [16].

According to a study, no significant association was found among the ApaI, BsmI, FokI, TaqI polymorphisms and DN risk in overall populations, the TaqI variants might related to DN susceptibility in Asians [17]. So, Detecting BDNF and TaqI gene polymorphisms and determining their harmful susceptibility to metabolic diseases will facilitate the emergence of breast cancer risk. Breast cancer incidence and consequence is strictly related to metabolic disorders. Therefore, managing these emerging risk factors should be one of the new and optimal strategies in the prevention and treatment of breast cancer [18].

Materials and Methods


The present case–control study was carried out in two groups. The control group was selected from 45 healthy individuals and the patient group was consisted of 80 patients with metabolic syndrome also diagnosed with breast cancer. The mean ages of patients and control group were (56.30 ± 1.367 years) and (51.54. ± 2.119 years) years, respectively. For the patient group, diagnosis and cancer status were confirmed by standardized questionnaire, pathological records and medical records obtained from Antalya State Hospital. The control subjects, who were not taking any regular medication by that time, were randomly selected among healthy volunteers. Stage of the BC were defined according to the American Joint Committee on Cancer (AJCC) TNM classification. Tumors were categorized in T1, T2, T3 and T4 subclasses according to the localization of the tumor. The study was approved by the Ethics Committee. The protocol followed was consistent with the World Medical Association Declaration of Helsinki (Ethical Principles for Medical Research Involving Human Subjects). Our study was approved by the Ethics Committee with protocol number 2020-488 [19].

DNA ısolation

Genomic DNA was extracted from peripheral whole blood containing EDTA according to salting-out technique. DNA was isolated from the blood leukocytes in 10 ml EDTA by the method of Miller et al. based on sodium dodecyl sulphate lysis, ammonium acetate extraction, and ethanol precipitation [20].

SNP detection

Polymorphism genotyping: The genomic DNA was obtained by using DNA isolation kit (Jena Bioscience, Jena, Germany), and the polymorphisms were determined by using polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP) method as previously reported [19]. Genotyping was performed by using TaqI endonuclease restriction enzymes both for BDNF gene G/A (rs6265) and VDR gene Taq I T/C (rs731236). The fragments were then visualized under UV light after ethidium bromide staining.

Statistical analysis

Statistical analysis was performed by using SPSS software package (revision 21.0; SPSS Inc., Armonk, NY, USA). Descriptive statics include the mean, standard deviation, and percentages. Mean values of differences in clinical parameters between patients and controls were compared with unpaired Student’s t-test and expressed as the mean ± standart deviation. The Hardy-Weinberg equilibrium was tested for all polymorphisms. Allele frequencies were estimated by gene counting methods. The Chi-square test was used to compare categorical distributions and differences in the distribution of genotypes and alleles between patients and controls. Values of p less than 0.05 were statistically considered as significant.


The present case–control study includes 80 breast cancer patients and 45 healthy individuals and the study groups have a similar distribution of age (p>0.05). The distribution of genotype and allele frequencies of VDR TaqI rs731236 polymorphisms in breast cancer patients and control groups were shown in Table 1. No significant associations were found between the development of breast cancer and VDR polymorphisms (p>0.05). Moreover, the clinical parameters were also not associated with VDR rs731236 genotypes and alleles (p>0.05) (Table 2).

Genotypes and Alleles Patient Control P-value
TaqI T/t n (%) n (%)
TT 33 (41.2) 19 (42.2)   0.845
Tt 40 (50) 24 (53.3)
tt 7 (8.8) 2 (4.4)
T Allel 106 (66.25) 62 (68.9) 0.669
t Allel 54 (33.75) 28 (31.1)

Table 1 Distribution of TaqI T/t rs731236 gene polymorphism results by genotype and alleles of breast cancer patients and controls.

Histopathological parameters Taq I  T/t P-value
N (%)
N (%)
N (%)
0.1.2 20 (47.6) 19(45.2) 3(7.1) 0.418
3 ve 4 10 (32.3) 18 (58.1) 3 (9.7)
Tumor Stage
T1 + T2 23 (42.6) 26 (48.1) 5 (9.3) 0.723
T3+ T4 7 (36.8) 11 (57.9) 1 (5.3)
Lymph node metastasis
N0 13 (39.4) 17 (51.5) 3 (9.1) 0.948
N1+N2 + N3 17 (42.5) 20 (50) 3 (7.5)
Estrogen Receptor
Yes 24 (40) 31 (51.7) 5 (8.3) 0.919
No 6 (46.2) & (46.2) 1 (7.7)
Progesterone Receptor
Yes 23 (40.4) 29 (50.9) 5 (8.8) 0.935
No 7 (43.8) 8 (50) 1 (6.2)
Yes 6 (50) 5 (41.7) 8.3% 0.776
No 24 (39.3) 32 (52.5) 5 (8.2)
Yes 15 (41.7) 19 (52.8) 2 (5.8) 0.862
No 15 (42.9) 17 (48.6) 3 (8.6)
Pre-menopause 15 (48.4) 14 (45.2) 2 (6.5) 0.542
Post-menopause 15 (35.7) 23 (54.8) 4 (9.5)
Yes 21 (48.8) 20 (46.5) 2 (4.7) 0.173
No 9 (30) 17 (56.7) 4 (13.3)
In situ component        
Noninvasion 19 (44.2) 21 (48.8) 3 (7)   0.937
Cell membrane 11 (36.7) 16 (53.3) 3 (10)
Pathological diagnosis
Ductal Invasion 19 (42.2) 22(48.9) 4 (8.9)   0.485
Lobuler Invasion 0 (0.0) 4 (100) 0 (0.0)
In-Situ 10(43.5) 11(47.8) 2(8.7)
Mucinous 30 (41.1) 37(50.7) 6(8.2)

Table 2 Distribution of TaqI T/t genotypes according to histopathological data in breast cancer patients.

Also, the distribution of genotype and allele frequencies of BDNF gene G/A (rs6265) polymorphisms in breast cancer patients and control groups were shown in Table 3. No significant associations were found between the development of breast cancer and BDNF polymorphisms (p>0.05). Moreover, the clinical parameters were also not associated with BDNF gene G/A (rs6265) genotypes and alleles (p>0.05) (Table 4). The comparison of 25-hydroxyvitamin D [25(OH) D] serum level among the study groups according to genotype distribution was shown in Table 5 and no significant association was found in terms of individual genotype. Also, in patient group, serum 25(OH)D levels (Table 6) according to demographic parameters as nodal status and metastasis demonstrated in Table 7.

Genotypes and Alleles
Patient Control P-value
  n (%) n (%)
GG 7 (8.8) 9 (20) 0.071
GA 73 (91.2) 36 (80)
AA 0 (0) 0 (0)
G Allel 87 (54.38) 54 (60) 0.389
A Allel 73 (45.63) 36 (40)

Table 3 Distribution of BDNF G/A polymorphism results by genotype and alleles of breast cancer patients and controls.

Histopathological Parameters BDNF G/A Genotypes


N (%)
N (%)
N (%)
P Değeri
0.1.2 0 (0) 38 (90.5) 4 (9.5) 0.637
3 ve 4 0 (0) 29 (93.5) 2 (6.5)
Tumor Stage
T1 + T2 0 (0) 50 (92.6) 4 (7.4) 0.647
T3+ T4 0 (0) 17 (89.5) 2 (10.5)
Lymph node metastasis
N0 0 (0) 29 (87.9) 4 (12.1) 0.4
N1+N2 + N3 0 (0) 38 (95) 2 (5)
Estrogen Receptor
Yes 0 (0) 54 (90) 6 (10) 0.583
No 0 (0) 13 (100) 0 (0)
Progesterone Receptor
Yes 0 (0) 53 (93) 4 (7) 0.606
No 0 (0) 14 (87.5) 2 (12.5)
Yes 0 (0) 10 (83.3) 2 (16.7) 0.254
No 0 (0) 57 (93.4) 4 (6.6)
Yes 0 (0) 33 (91.7) 3 (8.3) 0.971
No 0 (0) 32 (91.4) 3 (8.6)
Pre-menopause 0 (0) 29 (93.5) 2 (6.5) 0.637
Post-menopause 0 (0) 38 (90.5) 4 (9.5)
Yes 0 (0) 41 (95.3) 2 (4.7) 0.221
No 0 (0) 26 (86.7) 4 (13.3)
In situ component
Noninvasion 0 (0) 41 (95.3) 2 (4.7) 0.106
Cell membrane 0 (0) 26 (86.7) 4 (13.3)
Pathological diagnosis
Ductal Invasion 0 (0) 41 (91.1) 4 (8.9) 0.007
Lobuler Invasion 0 (0) 4 (100) 0 (0)
In-Situ 0 (0) 22 (95.7) 1 (4.3)
Mucinous 0 (0) 0 (0) 1 (100)

Table 4 Distribution of BDNF G/A genotypes in breast cancer patients according to the histopathological data of the patients.

Genotypes N Mean ±  SE
TT 33 17.503 ± 2.000
Tt 38 15.8216 ± 1.8749
tt 7 8.9743 ±  1.104

Table 5 Vitamin D serum levels by genotype frequencies.

Variables N Mean  ±  SE
Size 73 157.79 ± 0.816
Weight 73 73.3973 ± 1.50085
BMI 1 28.0000.
Fasting blood sugar 80 106.1750 ± 2.83780
Smoking history (pack/year) 16 5.5000 ± 0.28868
HGBA1C 64 6.0287 ± 0.09873
Calcium 80 9.4650 ± 0.05162
Albumin 80 4.2712 ± 0.03681
Total cholesterol 79 216.8608 ± 4.36707
HDL 79 54.6962 ± 1.24483
LDL 79 130.8861 ± 3.98084
Triglyceride 79 171.5696 ± 10.37081
Serumdemir 79 75.7342 ± 3.34089
Iron binding capacity 79 380.3797 ± 7.21374
Transferrin 79 279.9367 ± 5.41337
Uric Acid 80 253600.000 ± 8109.09788
FT4 78 0.8587 ± 0.02824
FT3 78 3.3324 ± 0.08452
CA153 79 18.5089 ± 3.59692
VIT D level 78 15.9185 ± 1.26694
VIT B 12 78 246.0256 ± 17.21206
Folic acid 78 10.6326 ± 0.44443
Ferritin 78 48.8846 ± 4.97617
Hemoglobin 80 12.9462 ± 0.14188
Mpv 80 8.60125 ± 0.098525
Neu 56 4392.86 ± 199.949

Table 6 Socio-demographics and Baseline laboratory results in the patient group.

Grup Patient (N) Mean ±  SE
0.1.2 41 16.1293 ± 1.63565
3 ve 4 30 16.6040 ± 2.34327
Lenf Nod
No 32 14.4625 ± 1.25854
N1+N2+N3 39 17.8621 ± 2.23368
T stage
T1+T2 53 17.1804 ± 1.667
T3+T4 18 13.8256 ± 2.10439
Metastasis  (+) -- --
Metastasis  (-) -- --
PR (+) 55 15.6749 ± 1.38713
PR (-) 16 18.5813 ± 3.73564
ES (+) 58 16.4879 ± 1.53753
ES (-) 13 15.6246 ± 2.93658
Her2 (+) 12 11.2350 ± 2.29782
Her2 (-) 59 17.3661 ± 1.53821
Ki67 (+) 35 16.4740 ± 2.42188
Ki67 (-) 34 16.5579 ± 1.35394
Pathological Diagnosis
In-Situ 23 14.360 ± 1.7467
Ductal Invasion 43 17.041 ± 1.9589
Premenopause 31 15.6342 ± 1.76299
Post-menopause 40 16.8690 ± 2.00182
Yes 15 13.5653 ± 2.0707
No 55 16.8625 ± 1.64017

Table 7 Vitamin D serum levels by clinical parameters.


In our study, it was aimed to determine whether BDNF and TaqI gene polymorphism can be used as a biomarker in determining the susceptibility to metabolic diseases. This study is an important study examining the relation of cardiovascular diseases, which are one of the most common metabolic diseases in the society, with BDNF and TaqI gene polymorphism. Also, we aimed that BDNF and TaqI gene variants, which are activity-suppressing alleles, and the potential role of TaqI to interact with other cell adhesion molecules as homophilic and heterophilic in metabolic diseases in breast cancer were investigated. In addition, the distribution of genotype and allele frequencies of BDNF gene G/A (rs6265) polymorphisms in breast cancer patients and control groups are shown in Table 3. There was no significant relationship between breast cancer development and BDNF polymorphisms (p>0.05). In addition, clinical parameters were not related to the BDNF gene G/A (rs6265) genotypes and alleles (p>0.05) (Table 4). The comparison of the serum level of 25-hydroxyvitamin D [25(OH)D] according to the genotype distribution between the study groups is shown in Table 5 and no significant relationship was found in terms of individual genotype. In addition, serum 25 (OH) D levels in the patient group according to demographic parameters such as nodal status and metastasis (Table 7) are shown in Table 7. Since there was no significant difference between the observed and expected values for the two alleles of each polymorphism, P-values were not statistically significant (p>0.005). It was investigated whether there was a possible relationship between the two main gene polymorphisms that were genotyped and biochemical parameters such as Glucose, Total Cholesterol, HDL-C, LDL-C and Triglyceride, which are used as markers in the pre-diagnosis of diseases and in CVD or T2DM diseases. According to the biochemistry results, the high value exceeding the upper limits of total cholesterol and triglyceride was prominent. For this reason, statistical significance was evaluated with the twotailed t-test method by using two values first (p>0.05). Statistical significance test includes the comparison of each parameter and BDNF and TaqI gene polymorphisms with all study groups. When looking at the possible link between BDNF and TaqI gene polymorphisms and glucose level and genotype distributions with glucose level (mg/dl) in the blood, it has been shown that patients with breast cancer have higher glucose levels despite using drugs that balance their insulin levels in the blood. When looking at serum glucose levels in patients with high glucose levels and BDNF and TaqI polymorphisms in patients, it can be said that the current increase may be due to this polymorphism, but it does not have statistical significance. Relationships between BDNF and TaqI polymorphisms and cholesterol, HDL-C and trigyliseride levels, which are other biochemical parameters other than glucose and LDL-C levels, were also examined. In the patient group, high levels of triglyceride and total cholesterol parameters prove that similar results can be considered, as with glucose.

In a total of 130 female individuals, allele frequencies of BDNF and TaqI polymorphisms were calculated, and the genotypes formed by alleles belonging to the BDNF and TaqI polymorphic regions (both of them BDNF G/A and TaqI T/t rs731236) did not show statistical significance according to the p-value, but the possible connection equations. According to the statistical results, the TaqI gene T/t allele is selected as the allele with more frequent frequency (TaqI alleles are 1.5-2 times higher than BDNF), and because of its strong effect, glucose, using estrogen and progesterone receptors, is effective on pathways. It gives clues that it causes instability in triglyceride and cholesterol levels. Looking at our results in terms of cardiovascular diseases, it suggests that high levels of high cholesterol, triglyceride and glucose levels may contribute to different researches as an explanatory biomarker in breast cancer susceptibility due to the difference in levels of alleles originating from TaqI from these polymorphisms.

According to genotype frequencies, the relationship between vitamin D levels and cardiovascular risk factors and vitamin D has been investigated, but the data we have are still insufficient to reach a definitive conclusion and no significant relationship was found between breast cancer. However, it is a known fact that the vitamin D response given by different cells in the same tissue is very heterogeneous [20]. In addition to the studied populations, different study groups have shown a significant relationship between TaqI polymorphism and diabetes [21]. A strong and significant correlation has been found between the blood glucose level and TaqI. This finding suggests that the TaqI polymorphism makes its mechanism of action through different pathways [22]. When we compared the glucose values of our participants with the BDNF and TaqI polymorphisms, we found that individuals genetically carrying the T-allele had lower glucose levels, but with the nucleotide change in the polymorphism region, the glucose levels of those carrying the C-allele increased, but there was no statistically significant difference.


Different study groups, as well as studied populations, have shown a significant link between TaqI polymorphism and diabetes. There is a strong and significant link between glucose and TaqI. It suggests that the TaqI polymorphism makes its mechanism of action through different pathways. By paying attention to these conditions, it will be possible to increase the quality of life standards with changes in lifestyle. Although it is important to identify individuals with metabolic diseases at an early age, the results of this study can be used as a guide to identify a risk factor to reduce the risk of intense lifestyle and associated cardiometabolic disease. Verification of this research with studies to be conducted with a wider patient population will also strengthen our results. Although it is important to determine the risk of developing breast cancer at an early stage, it can be said that the development of breast cancer in patients with metabolic disease is not directly related to BDNF and TaqI gene polymorphisms.

We believe that a wider patient group and a larger number of gene polymorphisms should be investigated, suggesting that reducing the risk of existing metabolic diseases and associated cardiometabolic diseases may reduce the risk of developing breast cancer. In addition, the validation of this research with further studies including the larger patient population and other related gene polymorphisms will strengthen our results. No significant association was found among the TaqI and BDNF polymorphisms with MetS in overall populations, the TaqI variants might related to other genes polymorfisms. Further researches are required to testify our meta-analysis.