Association of MTHFR Gene Variants (rs1801133 and rs1801131) with Serum Trace Elements Copper and Zinc and Biochemical Parameters (Homocysteine, Folic Acid, and Vitamin B12) in Individuals with Short Stature

Association of MTHFR Gene Variants (rs1801133 and rs1801131) with Serum Trace Elements Copper and Zinc and Biochemical Parameters (Homocysteine, Folic Acid, and Vitamin B12) in Individuals with Short Stature | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of MTHFR Gene Variants (rs1801133 and rs1801131) with Serum Trace Elements Copper and Zinc and Biochemical Parameters (Homocysteine, Folic Acid, and Vitamin B12) in Individuals with Short Stature Abhay Kumar Yadav, Ankur Singh, Ashish Ashish, Nitish Kumar Singh, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6516790/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Human height generally follows a normal distribution; thus, short stature is defined as height below the 3rd percentile or 2 standard deviations (SD) from the mean. Homocysteine metabolism, which involves folate and vitamin B12, is regulated by the methylenetetrahydrofolate reductase (MTHFR) enzyme. This study aimed to investigate the association of MTHFR polymorphisms with trace elements (copper and zinc), homocysteine, folic acid, and vitamin B12 in children with short stature. Methods: A total of 280 participants (130 short stature cases and 150 healthy controls), aged 4–12 years, were included. Serum homocysteine, folic acid, and vitamin B12 were measured using ELISA. MTHFR polymorphisms (rs1801133 and rs1801131) were genotyped using TaqMan® SNP Genotyping Assay via RT-PCR. Copper and zinc levels were measured by atomic absorption spectrophotometry. Results: The MTHFR rs1801133 polymorphism showed a significant association with short stature, with individuals carrying the TT genotype exhibiting higher homocysteine levels (26.3 ± 9.6 µmol/L), and lower folic acid (22.4 ± 4.3 ng/mL) and B12 levels (194.4 ± 27.9 pg/mL) compared to controls (p < 0.001). The TT genotype was also associated with higher copper (110.4 ± 14.94 µg/dL) and lower zinc levels (65.88 ± 16.69 µg/dL) in cases versus controls (p < 0.001). No significant association was observed for rs1801131. Conclusion: The MTHFR rs1801133 (TT genotype) is associated with elevated homocysteine, altered trace elements, and increased risk of short stature. These findings highlight the role of genetic and nutritional factors in growth regulation. Homocysteine MTHFR Short stature Genotyping Copper Zinc Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Human height is a typical trait with a normal distribution in the population. For that reason, short stature is defined as a height that has less than the 3rd percentile or 2SD (standard deviation) ( 1 ). Various causes of short stature like growth hormone deficiency, turner syndrome, Prader-Willi syndrome, and defects in the SHOX genehave been implicated ( 2 ) Since the 19th century, a strong association between the height of an individual and related diseases and mortality has been unraveled ( 3 ). A study from the insurance industry illustrated at the beginning of the 20th century that people with higher height lived longer in comparison to people with a smaller height ( 4 ).Normal human growth and development depend on metabolic pathways and cell differentiation, which require essential enzymes, such as MTHFR. MTHFR is a key enzyme that regulates folate metabolism, which is essential for cell metabolism, as well as DNA, RNA, and protein methylation ( 5 ).MTHFR cytogenetic location found on the short arm of chromosome 1p36.3 ( 6 ). In the case of genetic mutation of the MTHFR gene, it reduces the enzyme activity of MTHFR reductase. It is the major cause of hyperhomocysteine. 5- Methyltetrahydrofolate is the primary donor of remethylation of homocysteine to methionine which is encoded by the MTHFR gene (Mechanism shown in Fig. 1 ). Two most common MTHFR Polymorphisms is C677T and A1298C, affect the enzymatic activity of MTHFR mainly due to the amino acid substitutions at Glu429Ala and Ala222Val, and also due to the C to T shift is responsible for decreasing the enzymatic activity (40%) MTHFR, which in turn leads to an increase of homocysteine in blood plasma ( 7 , 8 , 9 ).Homocysteine is a sulfhydryl-containing amino acid that is an intermediate product of the normal biosynthesis of methionine and cysteine amino acids ( 10 ). Homocysteine metabolism is regulated by vitamin B12 and various enzymes like methionine synthase. Hyperhomocysteineimpairs the synthesis of Vitamin B12, which causes chronic disease ( 11 ). Maternal Vitamin B12 aids fetal growth and development, as well as the synthesis and stability of nucleic acid and DNA methylation, both of which are essential for gene regulation and expression ( 12 ). Vitamin B12 deficiency also cause blood anemia and malabsorption leads to gastrointestinal and autoimmune disease ( 13 ).Essential trace elements, such as zinc (Zn) and copper (Cu), play a vital role in the physical and physiological development of children and are closely associated with height and growth ( 14 ). Zinc, an essential trace element, plays a crucial role in the growth and development of children. It is involved in various physiological processes, including cell growth, immune function, gene regulation particularly of insulin-like growth factor and neurotransmission. Additionally, zinc acts as an antioxidant within the body ( 15 ). Zinc acts as a cofactor in enzymes involved in folate metabolism, including supporting the function of methionine synthase ( 16 ). Copper is essential for several physiological functions in a child’s body, including brain development, glucose metabolism, iron transport, and the maturation of both red and white blood cells ( 17 ). The frequency of MTHFR (rs1801133 and rs1801131) polymorphism has already been reported in several studies in various countries from different types of disease ( 18 , 19 , 20 , 21 , 22 ), but not in short stature.The socio-economically weaker countries suffer more from short-stature phenotypes than others.That is, according to reports, the polymorphisms rs1801131 and rs1801133 are more common among South Asians as well as associated with the MTHFR enzyme Activity ( 23 , 24 , 25 , 26 )shown in Fig. 2 .Thus, building on previous research, we conducted this study on short stature to investigate the association between MTHFR polymorphisms (rs1801131 and rs1801133) and the levels of homocysteine, folate, vitamin B12, as well as the trace elements copper and zinc in the population of Eastern Uttar Pradesh and Bihar. Materials and Methods Sample Selection: We recruited a total of 280 samples, of which 130 were cases, and 150 were control samples.The study was ethically approved by the ethical committee of the Institute of Medical Sciences, Banaras Hindu University (Ethical No. Dean/2020/EC/2035), and consent was obtained from theparents. Height in centimeters was taken using a calibrated wall-mounted stadiometer (Meddey Technologies Pvt Ltd). Weight in kilogram was taken using a digital weighing machine (IndoSugicals, India). The BMI calculation was based on the formula: weight in kilograms (kg) divided by height in meters (m) squared. Venipuncture blood samples were collected from the Pediatrics Department of IMS BHU in EDTA and Plane vial for DNA isolation and Serum separation. Inclusion criteria: The study focused on balanced samples of males and females aged 4 to 12 years with short stature. The selection criteria were based on physical and clinical parameters, including height, weight, BMI, and Z-scores, calculated using the WHO Peditools Growth CDC2-20 years charts. Participants were considered to have short stature if their height fell below the 3rd percentile or less than 2 standard deviations below. Exclusion criteria: Children who were excluded include those with chronic and endocrine disorders, as well as those with skeletal abnormalities such as achondroplasia and hypochondroplasia, and those with chromosomal abnormalities. DNA Extraction and MTHFR Genotyping (rs1801131, rs1801133): Blood samples were collected in K3 coated EDTA vial. Samples were process according to the kit protocol. DNA was isolated from the Invitrogen kit (catalogue no- K1820-01). Kit lysis buffer was used to lyse RBC and WBC cells, and after lysis, the sample was placed on the column and centrifuged at 1000 RPM for 1 min. After the process was done, the kit protocol followed column washing and elution. DNA quantification was done using spectroscopy (Epoch/2 microplate reader instruments). Whose Purity ratio was 260/280.The rs1801131 and rs1801133 Genotypic polymorphism was done using the kit Applied Biosystems by Thermo Fisher Scientific (TaqMan ®SNP Genotyping Assay). Oligonucleotide primers and hybridization TaqMan probes were designed by Applied Biosystems, Thermo Fisher Scientific, USA. The sequences of oligonucleotide primers assay with assay ID C_1202883_20, the SNP ID rs1801133 is located on chromosome 1 at position 11796321 (based on build GRCh38), exhibiting a G/A transition substitution within the Context sequence GAAAAGCTGCGTGATGATGAAATCG[G/A] CTCCCGCAGACACCTTCTCCTTCAA, and rs1801131AssayIDC_850486_20AAGAACGAAGACTTCAAAGACACTT[G/T]CTTCACTGGTCAGCTCCTCCCCCCA Where Allele 1 is represented by VIC and Allele 2 is represented by FAM (VIC: Victoria green fluorescent protein; FAM: fluorescein amide) in figure3.We had taken 50 ng of pure DNA sample for reaction setup and per reaction sample volume was maintained by following the composition 2X Taqman Assay Buffer 5 µl, 20x rs Assay 0.5 µl and DNA template 0.5 µl final volume was maintained by adding 4 µl of nuclease free water to the 10 µl total reaction volume. Real time-PCR was performed by instrument (Bio-red CFX96 real- time PCR). Denaturation was done at (92 0 C for15 sec) annealing and extension took place at 60 0 C for 1min and amplification was performed for 40 cycles. Biochemical analysis: Serum was isolated at 3,000 rpm for 5 minutes and stored frozen at -80 0 C until analysis was done. Homocysteine levels were measured by an enzyme-linked immunosorbent assay kit (BT lab catalogueE3292Hu). 50 µl of the sample was added to the ELISA microplate, and incubation was done at 37 0 C for 45 minutes. After the sample incubation, washing was done three times with a wash buffer, and during this time, a 50 µl biotin-labeled Antibody working solution was prepared. After incubating with the added secondary antibody for 30 minutes, the plate was washed according to the kit protocol, followed by enzyme conjugation to stop the reaction, and the OD was taken at 450 nm. Folic acid detection was done using the BT lab ELISA kit, and the catalogue number was (EA0051Hu). Vitamin B12 was detected using the BT lab Elisa kit, and the catalogue number was (EA0055Hu). Standard preparation: Standard solutions for copper (Lot #: 25-154CUX1) and zinc (Lot #: 25-145ZNX1) were used to generate the calibration curves. A stock solution with a concentration of 1000 µg/mL was serially diluted to obtain working standards of 20, 40 and 60 µg/dL. All glassware and plastic containers used in the preparation were thoroughly cleaned with 1% nitric acid, rinsed three times with deionised ultrapure water, and air-dried carefully to prevent contamination Zinc and copper measurement: The concentrations of copper (Cu) and zinc (Zn) in the samples were determined using an Atomic Absorption Spectrophotometer (PinAAcle 900 T). To prepare each sample, 200 µL of plasma was mixed with 800 µL of a diluent consisting of 1% nitric acid (HNO₃) and 0.4% Triton X-100 mili-Q water, resulting in a final volume of 1 mL. Measurements were performed using a graphite furnace (GTA-97 unit), with calibration curves that were established from standards prepared in a 1% HNO₃ nanoparticle solution. Element-specific Lumina hollow cathode lamps for copper and zinc (PerkinElmer, manufactured in Singapore) were used during the analysis Insilico prediction of Protein structure The 3D structures of Methionine Synthase, Cystathionine Gamma-Lyase, and Cystathionine Beta-Synthase were retrieved from the Protein Data Bank (PDB). These protein structures did not contain bound metal ions in their original form. Water molecules and heteroatoms were removed, missing hydrogen atoms were added, and structures were optimized using Discovery Studio Visualizer 2021. Metal Binding Docking Using MIB2 The docking of Zn²⁺ (for Methionine Synthase) and Cu²⁺ (for Cystathionine Gamma-Lyase and Beta-Synthase) was performed using the MIB2 (Metal Ion-Binding Site Prediction and Docking) server. MIB2 predicts potential metal-binding sites based on structural alignment with known metalloprotein templates and docks metal ions accordingly. The server outputs the predicted metal-binding residues and estimated binding energies. Visualization and Analysis The docked complexes obtained from MIB2 were visualized and analyzed using Discovery Studio Visualizer 2021. The key interacting residues involved in metal coordination were identified, and the docking poses were visually confirmed. Statistical analysis: Descriptive statistics were done using GraphPad Prism 8.4.0. Kolmogorov-Smirnov test was used on the Biomarker dataset and was found to be significant, indicating that the data were normally distributed. Data were normally distributed continuous variables biomarker homocysteine, vitamin B12, and folic acid was done by independent samples t-test. A two-tailed P less than 0.05 was considered statistically significant. The Mann-Whitney test was performed to analyze trace element levels between the case and control groups. Two-way Chi-square test was done for Hardy-Weinberg equilibrium to calculate the case's and control's genotype frequency. The comparison of homocysteine across rs1801133 genotypes was performed using a one-way ANOVA, with a p-value of less than 0.05 indicating statistical significance. Additive, dominant, and recessive models for short stature and control groups were analyzed using multiple logistic regressions. Odds ratios, 95% confidence intervals, and p-values were calculated. Spearman correlation analysis was performed to assess the relationships between copper, zinc, homocysteine, folic acid, and vitamin B12 levels. Stepwise regression analysis predicting Cu and Zn was conducted using IBM SPSS 2020. Result The present study compared the distribution of MTHFR genotypes (C677T and A1298C) and alleles between a short-stature group (N =130) and a control group (N =150). The frequencies of all the genotype and alleles of all the polymorphisms fall under the Hardy- Weinberg equilibrium in the controls. The MTHFR genotype rs1801133 was found to be significant, with a P-value of 0.01. The frequency of the rs1801133 T allele was 37.3% in cases and 24.6% in controls, respectively (odds ratio = 0.609, 95% CI: 0.42–0.87, P = 0.01). Between the two restriction sites, rs1801133 was significantly associated with short stature between cases and control samples. In contrast, the genotype rs1801131 (A1298C) was not significant, with a P-value of 0.09. The frequency of the C allele for rs1801131 in cases and controls was 31.53% and 26.33%, respectively. Statistically, no significant difference was observed for MTHFR rs1801131 (A1298C) between short-stature cases and controls. The allelic frequency analysis of MTHFR rs1801131 yielded an odds ratio of 0.789 (95% CI: 0.54–1.13, P = 0.205), indicating no association with short stature in the control group. The genotypic and allele frequency classification of MTHFR rs1801133 (C677T) and rs1801131 (A1298C) among cases and controls is shown in Table 1. In table.2 in our analysis of rs1801133, significant associations were observed across all models. The additive model yielded an odds ratio (OR) of 1.737 (95% CI: 1.218–2.477, P = 0.002), indicating that each additional copy of the risk allele increased the odds of the outcome. The dominant model also showed a significant association, with an OR of 1.832 (95% CI: 1.139–2.946, P = 0.012), suggesting that higher likelihood of the outcome in individuals carrying at least one risk allele. The recessive model demonstrated the strongest association, with an OR of 2.852 (95% CI: 1.296–6.275, P = 0.009), indicating nearly a threefold increase in odds for individuals with two copies of the risk allele. In contrast, the analysis of rs1801131 showed weaker associations. The additive model produced an OR of 1.229 (95% CI: 0.872–1.731, P = 0.237), which was not statistically significant. The dominant model approached not significance with an OR of 1.556 (95% CI: 0.969–2.499, P = 0.066). However, the recessive model did not show a significant association, with an OR of 0.885 (95% CI: 0.421–1.858, P = 0.746). Table1. MTHFR (rs1801133 and rs1801131) polymorphism in among short stature and controls group. Variable Short stature group (%) (n= 130) Control group (%) (n= 150) Chi square χ 2 Odds Ratio (95 % CI) P value MTHFR (C677T) Genotype CC 55 (42.3) 86 (57.3) CT 53 (40.7) 54 (36) 9.9 0.01 TT 22 (16.9) 10 (6.6) Allele C 163 (62.6) 226 (75.3) 0.609 (0.42 – 0.87) 0.01 T 97 (37.3) 74 (24.6) MTHFR (A1298C) Genotype AA 62 (47.69) 88 (58.66) AC 54 (41.53) 44 (29.33) 4.62 0.09 CC 14 (10.76) 18 (12.00) Allele A 178 (68.46) 220 (73.33) 0.789 (0.54 – 1.13) 0.205 C 82 (31.53) 80 (26.33) Table2. The MTHFR rs1801133 and rs1801131 frequencies of alleles and genotypes were investigated, consisting of 130 samples of short stature and 150 control samples utilizing additive, dominant and recessive models. Restriction site (rs) Models Coefficient Odds ratio Mean Standard deviation P- value 95 % Confidence interval rs1801133 rs1801131 Additive 0.552 1.737 0.610 0.682 0.002 1.218 – 2.477 Dominant 0.6056 1.832 0.496 0.499 0.012 1.139 – 2.946 Recessive 1.048 2.852 0.114 0.318 0.009 1.296 – 6.275 Additive 0.2063 1.229 0.578 0.687 0.237 0.872- 1.731 Dominant 0.4426 1.556 0.464 0.498 0.066 0.969 – 2.499 Recessive -0.1221 0.885 0.114 0.318 0.746 0.421 – 1.858 In the table.3 significant differences were observed in the levels of homocysteine, folic acid, vitamin B12, zinc, and copper between individuals with short stature (n = 130) and healthy controls (n = 150). Homocysteine levels were markedly higher in the short stature group (17.22 ± 7.9 nmol/ml) compared to controls (12.84 ± 3.2 nmol/ml), with a highly significant p-value of 0.001, indicating elevated homocysteine may be associated with short stature. Conversely, levels of folic acid and vitamin B12 were significantly lower in the short stature group (37.45 ± 10.6 nmol/L and 260.8 ± 76.18 ng/L, respectively) than in controls (42.75 ± 7.09 nmol/L and 294.6 ± 46.9 ng/L), both with p-values of 0.001. Additionally, zinc levels were significantly reduced in the short stature group (90.22 ± 24.7 µg/dl) compared to controls (100.1 ± 18.01 µg/dl; p = 0.006), while copper levels were significantly elevated (95.08 ± 17.06 µg/dl vs. 86.11 ± 15.2 µg/dl; p = 0.001). Table3. Serum level of homocysteine, folic acid and vitamin B 12, Zinc and Copper in Short stature and control samples. Parameter Short stature N = 130 Control N = 150 P – value Homocysteine (nmol/ml) 17.22 ± 7.9 12.84 ± 3.2 0.001 Folic acid (nmol/L) 37.45 ± 10.6 42.75 ± 7.09 0.001 Vitamin B 12 (ng/L) 260.8 ± 76.18 294.6 ± 46.9 0.001 Zinc (µg/dl) 90.22 ± 24.7 100.1 ± 18.01 0.006 Copper (µg/dl) 95.08 ± 17.06 86.11 ± 15.2 0.001 Data represented with a mean ± standard deviation and a p-value of less than 0.05 indicates statistical significance. In table.4 The analysis of MTHFR C677T genotypes (CC, CT, TT) in relation to homocysteine, folic acid, and vitamin B12 levels revealed distinct biochemical differences between short stature individuals (n = 130) and controls (n = 150). Among individuals with the CC genotype, no significant differences were observed between short stature and control groups in homocysteine (12.3 ± 2.7 vs. 11.1 ± 2.9 nmol/mL; p = 0.103), folic acid (47.06 ± 3.6 vs. 48.12 ± 3.4 nmol/L; p = 0.269), or vitamin B12 levels (329.2 ± 10.9 vs. 333.5 ± 28.9 ng/L; p = 0.470). Similarly, in the CT genotype group, differences in homocysteine (15.4 ± 2.8 vs. 14.1 ± 3.1 nmol/mL; p = 0.082), folic acid (39.6 ± 2.9 vs. 40.6 ± 2.4 nmol/L; p = 0.158), and vitamin B12 (280.1 ± 21.7 vs. 281.1 ± 27.1 ng/L; p = 0.870) between the two groups were not statistically significant. However, individuals with the TT genotype showed significantly elevated homocysteine levels in the short stature group compared to controls (26.3 ± 9.6 vs. 14.2 ± 2.1 nmol/mL; p = 0.001), along with significantly reduced folic acid (22.4 ± 4.3 vs. 31.3 ± 7.1 nmol/L; p = 0.001) and vitamin B12 levels (194.4 ± 27.9 vs. 223.8 ± 23.17 ng/L; p = 0.001). Table4.Comparison of the MTHFR rs1801133 gene polymorphism with homocysteine,folic acid, and vitamin B12 levels. Genotype MTFHR C677T N= 130 n= 150 Homocysteine (nmol/mL) P- value Folic acid (nmol/L) P-value Vitamin B 12 (ng/L) P-value Short Stature Control Short Stature Control Short Stature Control CC N= 55 n = 86 12.3 ± 2.7 11.1 ± 2.9 0.103 47.06± 3.6 48.12± 3.4 0.269 329.2 ± 10.9 333.5± 28.9 0.470 CT N= 53 n = 54 15.4 ± 2.8 14.1 ± 3.1 0.082 39.6± 2.9 40.6± 2.4 0.158 280.1 ± 21.7 281.1 ± 27.1 0.870 TT N= 22 n = 10 26.3 ± 9.6 14.2 ± 2.1 0.001 22.4± 4.3 31.3± 7.1 0.001 194.4± 27.9 223.8 ± 23.17 0.001 In The table.5 MTHFR C677T genotypes and trace element levels (zinc and copper) was examined in individuals with short stature (n = 130) and controls (n = 150). In the CC genotype group, zinc and copper levels did not show significant differences between short stature individuals and controls, with zinc levels at 105.2 ± 14.7 µg/dl and 108.3 ± 16.09 µg/dl (p = 0.292), and copper levels at 92.56 ± 14.17 µg/dl and 89.42 ± 15.42 µg/dl (p = 0.689), respectively. Similarly, the CT genotype group also showed no significant differences, with zinc levels at 93.45 ± 24.15 µg/dl in short stature individuals and 96.41 ± 18.23 µg/dl in controls (p = 0.817), and copper levels at 88.37 ± 16.55 µg/dl and 84.75 ± 17.68 µg/dl (p = 0.326), respectively. However, a significant difference was observed in the TT genotype group. Individuals with short stature had markedly lower zinc levels (65.88 ± 16.69 µg/dl) compared to controls (86.77 ± 10.65 µg/dl; p = 0.001), and significantly higher copper levels (110.4 ± 14.94 µg/dl vs. 80.25 ± 8.03 µg/dl; p = 0.001). Table5.Comparison of the MTHFR rs1801133 gene polymorphism with homocysteine,folic acid, and vitamin B12 levels. Genotype MTFHR C677T N= 130 n= 150 Zinc (µg/dl) P-value Copper (µg/dl) P-value Short Stature Control Short Stature Control CC N= 55 n = 86 105.2 ± 14.7 108.3 ± 16.09 0.292 92.56 ± 14.17 89.42 ± 15.42 0.689 CT N= 53 n = 54 93.45 ± 24.15 96.41 ± 18.23 0.817 88.37 ± 16.55 84.75 ± 17.68 0.326 TT N= 22 n = 10 65.88 ± 16.69 86.77 ± 10.65 0.001 110.4 ± 14.94 80.25 ± 8.03 0.001 Table 6 and Figure 4 the Correlation analysis within individuals carrying the TT genotype of the MTHFR rs1801133 polymorphism (n = 22) revealed significant associations between trace element levels (zinc and copper) and biochemical markers. Homocysteine levels showed a strong negative correlation with zinc (r = -0.805, p = 0.001) and a strong positive correlation with copper (r = 0.747, p = 0.001), suggesting that higher homocysteine levels are associated with reduced zinc and elevated copper. Folic acid demonstrated a moderate positive correlation with zinc (r = 0.471, p = 0.02) and a moderate negative correlation with copper (r = -0.517, p = 0.01). Vitamin B12 levels were positively correlated with zinc (r = 0.749, p = 0.001) and negatively correlated with copper (r = -0.448, p = 0.03). Table.6.Correlation analysis of MTHFR rs1801133 gene polymorphism with levels of homocysteine, folic acid, vitamin B12, zinc, and copper Variables (TT Genotype) N= 22 Zinc (µg/dL) Copper (µg/dL) Correlation coefficient (r) P value Correlation coefficient (r) P value Homocysteine (nmol/ml) -0.805 0.001 0.747 0.001 Folic acid (nmol/L) 0.471 0.02 - 0.517 0.01 Vitamin B 12 (ng/L) 0.749 0.001 -0.448 0.03 Table.7.Regression Analysis Predicting Cu (Copper) The regression analysis predicting copper (Cu) levels revealed that homocysteine was a significant predictor, B = 1.156, SE = 0.229, β = 0.748, t(20) = 5.045, p < 0.001. The model accounted for 56.0% ofthe variance in Cu levels (R² = 0.560, Adjusted R² = 0.538), indicating a strong predictive relationship. The overall model was statistically significant, F(1,20) = 25.453, p < 0.0001, suggesting that homocysteine levels are crucial in determining Cu concentrations. The positive regression coefficient implies higher homocysteine levels are associated with increased Table 8. Regression Analysis Predicting Zn (Zinc). Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 101.610 6.670 15.233 .000 homocysteine -1.357 .238 -.786 -5.691 .000 2 (Constant) 55.027 18.705 2.942 .008 homocysteine -.942 .263 -.546 -3.584 .002 B12 .239 .091 .399 2.623 .017 Note:R² (Model 1, 2): 0.618, 0.720,Adjusted R² (Model 1, 2): 0.538, 0.690, F-statistic (Model 1, 2): 32.390, 6.878, p-value (Model 1, 2):< .0001, .017 The regression analysis table provides insights into how variables such as homocysteine and B12 predict zinc (Zn) levels. In Model 1, the constant (intercept) is significantly positive (B = 101.610, t = 15.233, p < .0001), suggesting that, when homocysteine is zero, zinc levels are predicted to be around 101.61. Homocysteine, however, has a significant negative effect on zinc levels (B = -1.357, t = -5.691, p < .0001), with the negative coefficient indicating that higher homocysteine levels are associated with lower zinc levels. In Model 2, the constant is again significantly positive (B = 55.027, t = 2.942, p = .008), while homocysteine continues to show a negative relationship with zinc (B = -0.942, t = -3.584, p = .002). Additionally, vitamin B12 (B = 0.239, t = 2.623, p = .017) has a positive and significant effect on zinc, suggesting that higher B12 levels are linked to higher zinc levels. The R² values (0.618 for Model 1 and 0.720 for Model 2) indicate that the models explain approximately 61.8% and 72% of the variability in zinc levels, respectively. The adjusted R² values (0.538 and 0.690) show that these models are fairly robust. The significant F-statistics (32.390 for Model 1 and 6.878 for Model 2) further support the overall significance of the models, with p-values indicating that both models are highly statistically significant which was shown in table.8 and figure.6. The docking results from MIB2 provided binding energy values and predicted residues involved in the coordination of Zn²⁺ and Cu²⁺ ions to the target proteins. The docked complexes were successfully visualized in Discovery Studio. The findings are summarized in the table below: Table. 9. This table shows the Zn²⁺ and Cu²⁺ binding energies and interacting residues in the enzymes Methionine Synthase, Cystathionine Gamma-Lyase, and Cystathionine Beta-Synthase. Complex Name Binding Energy Binding Residues Methionine Synthase – Zn²⁺ –7.74 kcal/mol CYS260, CYS323, CYS324, ASN287 Cystathionine Gamma-Lyase – Cu²⁺ –6.64 kcal/mol ARG161, GLU131 Cystathionine Beta-Synthase – Cu²⁺ –6.72 kcal/mol ARG132, ASP129 Among the docked complexes, Methionine Synthase with Zn²⁺ showed the highest binding affinity (–7.74 kcal/mol), suggesting a strong coordination between the zinc ion and cysteine/asparagine residues. The copper-binding proteins also showed favorable binding energies and conserved interaction residues predicted by MIB2 in table.9. Discussion The present study investigated the association between MTHFR polymorphisms rs1801133 (C677T) and rs1801131 (A1298C) with short stature in 130 cases and 150 controls. All genotypic distributions adhered to Hardy-Weinberg equilibrium among controls. The rs1801133 T allele was significantly more prevalent in short-stature individuals (37.3%) than in controls (24.6%), with an odds ratio (OR) of 0.609 and P = 0.01, suggesting it as a potential risk factor for short stature. This polymorphism demonstrated significant associations across additive (OR = 1.737, P = 0.002), dominant (OR = 1.832, P = 0.012), and recessive (OR = 2.852, P = 0.009) models, reinforcing its potential role in growth impairment. Conversely, rs1801131 did not exhibit a significant association, with the C allele frequency at 31.53% in cases versus 26.33% in controls (OR = 0.789, P = 0.205). The additive, dominant, and recessive models for rs1801131 were also non-significant. These findings align with recent studies indicating that the MTHFR C677T variant may influence conditions related to growth and development. For instance, a case report identified a novel MTHFR mutation associated with hyperhomocysteinemia, presenting as tall stature and skeletal abnormalities, underscoring the enzyme's role in growth regulation (27). Additionally, research has linked the MTHFR C677T variant to altered folate metabolism, which is crucial for DNA synthesis and methylation processes vital for normal growth (28). The biochemical analysis in the present study revealed significant alterations in key metabolic parameters among individuals with short stature compared to healthy controls, suggesting a potential link between micronutrient imbalances and impaired growth. Elevated homocysteine levels in the short stature group (17.22 ± 7.9 nmol/ml vs. 12.84 ± 3.2 nmol/ml; p = 0.001) may reflect disrupted folate and vitamin B12 metabolism, as both were significantly lower in cases (37.45 ± 10.6 nmol/L and 260.8 ± 76.18 ng/L, respectively) than controls (42.75 ± 7.09 nmol/L and 294.6 ± 46.9 ng/L; p = 0.001), supporting the role of these vitamins in one-carbon metabolism and growth. Similar associations have been observed in previous studies, where elevated homocysteine and low B-vitamin levels were linked to growth retardation and developmental delays (29). Moreover, the study found significantly reduced zinc and elevated copper levels in the short stature group, which aligns with existing literature highlighting zinc deficiency as a risk factor for growth failure and the antagonistic relationship between zinc and copper in maintaining metabolic balance (30,31). These findings underscore the importance of monitoring and addressing nutritional and metabolic imbalances in children with growth impairments.Recent studies havecorroborated these associations relationship between MTHFR polymorphisms, homocysteine, folic acid, and vitamin B12 levels in pregnant women.They found significant associations between vitamin B12 and folic acid levels with homocysteine concentrations, where lower serum levels of these vitamins were linked to higher homocysteine levels.Interestingly, no significant association was observed between MTHFR genetic polymorphisms and serum homocysteine levels, likely due to folic acid and vitamin B12 supplementation during pregnancy, which may mitigate the mutation's effects (32) . Additionally, a study highlighted a significant association between the MTHFR C677T TT genotype and vitamin B12 deficiency.They reported that individuals with the TT genotype had a higher prevalence of vitamin B12 deficiency compared to those with CC or CT genotypes.This deficiency was also linked to elevated homocysteine levels and endothelial dysfunction, emphasizing the clinical significance of this genetic variant. These findings underscore the importance of monitoring and managing vitamin B12 and folic acid levels in individuals with the MTHFR C677T TT genotype to mitigate potential health risks (33).In individuals carrying the TT genotype of the MTHFR rs1801133 polymorphism, a significant correlation was observed between trace elements and biochemical markers, indicating a genotype-dependent interplay affecting metabolic balance. Elevated homocysteine levels were strongly associated with decreased zinc and increased copper levels, consistent with findings that MTHFR C677T homozygosity impairs enzyme function, leading to hyperhomocysteinemia and redox imbalance (34,35). The observed correlations of folic acid and vitamin B12 with zinc and copper further highlight the interconnectedness of one-carbon metabolism and trace element homeostasis. Prior studies have shown that zinc plays a critical role in methionine synthase function and DNA methylation, processes disrupted in folate and B12 deficiency (36). Moreover, excess copper has been linked to oxidative stress, which can exacerbate folate cycle dysfunction in genetically predisposed individuals (37). A recent study reported altered zinc and copper levels in individuals with MTHFR polymorphisms, reinforcing the metabolic vulnerability conferred by the TT genotype. These associations suggest that maintaining optimal trace element levels might mitigate metabolic disturbances and should be considered in nutritional strategies for individuals with MTHFR C677T homozygosity (38).The regression model demonstrated that homocysteine is a significant predictor of copper (Cu) levels, suggesting a mechanistic link between homocysteine metabolism and copper homeostasis. With a positive regression coefficient (B = 1.156, β = 0.748, p < 0.001), the model accounted for 56.0% of the variance in copper levels (R² = 0.560), indicating that elevated homocysteine concentrations are strongly associated with increased copper accumulation. This relationship may be explained by the pro-oxidant nature of both homocysteine and copper. Homocysteine can induce oxidative stress by generating reactive oxygen species (ROS) and reducing the availability of antioxidant defenses, while copper, especially in its free ionic form, participates in Fenton-like reactions that exacerbate oxidative damage (39,40). The findings align with previous reports indicating a biochemical crosstalk between copper metabolism and one-carbon metabolism pathways, with potential implications for vascular, neurological, and metabolic disorders (41, 42). This model reinforces the need to consider trace element dynamics in conditions associated with elevated homocysteine.The regression analysis highlights the interconnected roles of homocysteine and vitamin B12 in modulating zinc (Zn) levels, offering key insights into trace element metabolism. Model 1 reveals a strong inverse association between homocysteine and zinc (B = -1.357, p < 0.0001), consistent with studies suggesting that elevated homocysteine disrupts zinc absorption and increases oxidative stress, which may deplete zinc reserves (43,44). In Model 2, this negative association remains (B = -0.942, p = 0.002), while vitamin B12 emerges as a significant positive predictor of zinc levels (B = 0.239, p = 0.017). This aligns with prior findings indicating that B12 plays a role in DNA synthesis, red blood cell formation, and proper absorption of trace elements like zinc (45,46). The high R² values in both models (0.618 and 0.720) reinforce the predictive strength and clinical relevance of these variables in regulating zinc status. These findings contribute to a growing body of evidence emphasizing the interaction between one-carbon metabolism and trace element regulation, with implications for nutritional interventions in populations at risk for micronutrient deficiencies and metabolic disorders (47,48). Based on our biochemical findings in TT genotype individuals—characterized by elevated homocysteine levels, low vitamin B12 and folic acid, decreased zinc, and increased copper we proposed a hypothesis that disruptions in trace element balance may compromise the activity of key enzymes in homocysteine metabolism. Specifically, we hypothesized that excess copper may negatively impact the enzymes of the transsulfuration pathway cystathionine beta-synthase (CBS) and Cystathionine Gamma-Lyase ( CGL), while zinc deficiency could impair methionine synthase (MS), a key enzyme in the remethylation pathway in figure.1. To test this, we performed molecular docking to explore how Cu²⁺ and Zn²⁺ interact with these enzymes at a structural level. Docking analysis revealed that Cu²⁺ binds to the CGL enzyme with a binding energy of –6.64 kcal/mol, primarily interacting with residues ARG161 and GLU131. For the CBS enzyme, Cu²⁺ showed a binding energy of –6.72 kcal/mol at residues ARG132 and ASP129. These interactions suggest that copper may interfere with the structural stability or catalytic activity of these enzymes, potentially contributing to impaired transsulfuration and homocysteine accumulation.In support of the role of zinc in remethylation, docking studies with methionine synthase and Zn²⁺ demonstrated a strong binding affinity of –7.74 kcal/mol, with key interactions at residues CYS260, CYS323, CYS324, and ASN287. These results suggest that zinc plays a stabilizing role in maintaining methionine synthase structure and function.Overall, our molecular docking findings provide structural insights that support our hypothesis: elevated copper and reduced zinc levels may disrupt the normal function of homocysteine-metabolizing enzymes, contributing to hyperhomocysteinemia in individuals with the TT genotype. Conclusion In our study, we found that the MTHFR rs180113 polymorphism was significantly associated with homocysteine levels. Individuals with the TT genotype exhibited higher homocysteine levels and lower levels of folic acid and B12 compared to those with CT and CC genotypes. Additionally, individuals with the TT genotype showed higher level of copper and lower level of Zinc in short stature group in compression of control group suggesting a potential link between trace elements and homocysteine metabolism.The increased homocysteine levels observed in individuals with short stature compared to controls further support the possible involvement of homocysteine metabolism in growth regulation. Moreover, the imbalance of trace elements, particularly copper and zinc appears to influence homocysteine levels. Given the multifactorial nature of short stature and metabolic disturbances further studies involving larger and more diverse cohorts are essential to validate and strengthen these associations. Declarations Ethical committee approval: Name of the ethical committee: Institute of Medical Science, Banaras Hindu University Declarations: Acknowledgement We want to extend our sincere gratitude to Multi-Disciplinary Research Units (MRUs) Laboratory, a grant by ICMR-Department of Health Research. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Ethics statement The studies involving human participants were reviewed and approved by Ethics Committee of the Institutional Ethical committee before starting the study (Ethical No. Dean/2020/EC/2035) Consent to Participate All research procedures were approved by and in accordance with relevant guidelines and regulations. Consent for publication Not available. Data Availability The detailed datasets analyzed during the current study are available with the corresponding author. In the future, it will be made available on reasonable request. Data are however available from the authors upon reasonable request. Funding Not available. Author contributions RS, and AS conceived and designed the project. AKY, AA, NKS, SV and ST performed all operations. AKM analysed the data and SM, PD, SS, JY drew the figures. ABY and RS wrote the manuscript. AS, AA, AKM and NKS revised the manuscript. All authors contributed to the article and approved the submitted version. References Grunauer M, Jorge AA. Genetic short stature. Growth Hormone & IGF Research. 2018 Feb 1; 38:29-33. Orso M, Polistena B, Granato S, Novelli G, Di Virgilio R, La Torre D, d’Angela D, Spandonaro F. Pediatric growth hormone treatment in Italy: A systematic review of epidemiology, quality of life, treatment adherence, and economic impact. Plos one. 2022 Feb 25; 17(2):e0264403. British Association for the Advancement of Science (1883) Final report of the Anthropometric Committee. 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03:53:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6516790/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6516790/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84781161,"identity":"06e3c6a2-7699-4f99-8b2d-d2e83e100126","added_by":"auto","created_at":"2025-06-17 09:32:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":94504,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of the role of the MTHFR enzyme and the involvement of homocysteine and trace elements during food nutrient metabolism.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6516790/v1/df73453d8eb183819ebb643e.png"},{"id":84780250,"identity":"53f582f5-f74b-44e4-9c68-e64869f5680d","added_by":"auto","created_at":"2025-06-17 09:24:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":12914,"visible":true,"origin":"","legend":"\u003cp\u003eThis figure shows the worldwide distribution of MTHFR polymorphism (rs1801133, rs1801131) frequency.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6516790/v1/b218b6d565e30914bc9d994d.png"},{"id":84780253,"identity":"8a750953-be5f-4504-a549-2bf7c3fdf157","added_by":"auto","created_at":"2025-06-17 09:24:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":351773,"visible":true,"origin":"","legend":"\u003cp\u003eshows the amplification of two alleles using fluorescent dyes.(A) shows allele 1 amplified with VIC dye, and (B) shows allele 2 amplified with FAM dye. (C) displays the simultaneous amplification of both alleles with VIC and FAM. The Y-axis represents Relative Fluorescence Units (RFU), indicating the fluorescence signal per cycle, while the X-axis shows the cycle number. (E) and (F) depict the allelic discrimination and polar distribution plots for the MTHFR rs1801133 variant. In the discrimination plot, data grouping is highlighted using a red circle: orange represents VIC-labeled homozygous allele 1, blue indicates FAM-labeled homozygous allele 2, and green corresponds to heterozygous samples containing both dyes.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6516790/v1/21441894c3dc0ae2f5104de5.png"},{"id":84781165,"identity":"f8fc22cf-08b9-4ae3-9112-e06460b231e3","added_by":"auto","created_at":"2025-06-17 09:32:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":165515,"visible":true,"origin":"","legend":"\u003cp\u003eFigure A, show the correlation between zinc and homocysteine. In Figures B and C, show the correlation of zinc with folic acid and vitamin B12, respectively. In Figures D, E, and F, show the correlation of copper with homocysteine, folic acid, and vitamin B12, respectively. Cu, levels. These findings highlight the potential biochemical link between homocysteine metabolism and copper regulation in given in table.7 and figure.5.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6516790/v1/b538b1fb4bad1c115b523177.png"},{"id":84781162,"identity":"a87222d8-327c-4351-89a9-454dd46abd00","added_by":"auto","created_at":"2025-06-17 09:32:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":33356,"visible":true,"origin":"","legend":"\u003cp\u003eThis figure shows the scattered plot of Copper.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6516790/v1/367e5d1c0f743e90638bdddd.png"},{"id":84780256,"identity":"a0511251-c5fa-4237-97e6-ad8e2bc8b310","added_by":"auto","created_at":"2025-06-17 09:24:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":38426,"visible":true,"origin":"","legend":"\u003cp\u003ethis figure show the scattered plot of Zinc.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6516790/v1/97ce4e9c73dd75f9020b5320.png"},{"id":84780261,"identity":"249c92b2-35dd-4dd2-b6c3-749c7e984611","added_by":"auto","created_at":"2025-06-17 09:24:16","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":660493,"visible":true,"origin":"","legend":"\u003cp\u003e(A)Predicted Zn²⁺ binding site in Methionine Synthase, (B) Cu²⁺ binding site prediction in Cystathionine γ-lyase, and (C) Cu²⁺ binding site prediction in Cystathionine β-synthase.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6516790/v1/95b2f8efcbdc4932e26d76c6.png"},{"id":85220902,"identity":"40bb9eff-0e58-4325-8786-6198e048aaa7","added_by":"auto","created_at":"2025-06-23 14:09:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2499977,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6516790/v1/371b5bc4-7169-48be-8603-9d46ee532c5b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of MTHFR Gene Variants (rs1801133 and rs1801131) with Serum Trace Elements Copper and Zinc and Biochemical Parameters (Homocysteine, Folic Acid, and Vitamin B12) in Individuals with Short Stature","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHuman height is a typical trait with a normal distribution in the population. For that reason, short stature is defined as a height that has less than the 3rd percentile or 2SD (standard deviation) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Various causes of short stature like growth hormone deficiency, turner syndrome, Prader-Willi syndrome, and defects in the SHOX genehave been implicated (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Since the 19th century, a strong association between the height of an individual and related diseases and mortality has been unraveled (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). A study from the insurance industry illustrated at the beginning of the 20th century that people with higher height lived longer in comparison to people with a smaller height (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).Normal human growth and development depend on metabolic pathways and cell differentiation, which require essential enzymes, such as MTHFR. MTHFR is a key enzyme that regulates folate metabolism, which is essential for cell metabolism, as well as DNA, RNA, and protein methylation (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).MTHFR cytogenetic location found on the short arm of chromosome 1p36.3 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In the case of genetic mutation of the MTHFR gene, it reduces the enzyme activity of MTHFR reductase. It is the major cause of hyperhomocysteine. 5- Methyltetrahydrofolate is the primary donor of remethylation of homocysteine to methionine which is encoded by the MTHFR gene (Mechanism shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Two most common MTHFR Polymorphisms is C677T and A1298C, affect the enzymatic activity of MTHFR mainly due to the amino acid substitutions at Glu429Ala and Ala222Val, and also due to the C to T shift is responsible for decreasing the enzymatic activity (40%) MTHFR, which in turn leads to an increase of homocysteine in blood plasma (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).Homocysteine is a sulfhydryl-containing amino acid that is an intermediate product of the normal biosynthesis of methionine and cysteine amino acids (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Homocysteine metabolism is regulated by vitamin B12 and various enzymes like methionine synthase. Hyperhomocysteineimpairs the synthesis of Vitamin B12, which causes chronic disease (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Maternal Vitamin B12 aids fetal growth and development, as well as the synthesis and stability of nucleic acid and DNA methylation, both of which are essential for gene regulation and expression (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Vitamin B12 deficiency also cause blood anemia and malabsorption leads to gastrointestinal and autoimmune disease (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).Essential trace elements, such as zinc (Zn) and copper (Cu), play a vital role in the physical and physiological development of children and are closely associated with height and growth (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Zinc, an essential trace element, plays a crucial role in the growth and development of children. It is involved in various physiological processes, including cell growth, immune function, gene regulation particularly of insulin-like growth factor and neurotransmission. Additionally, zinc acts as an antioxidant within the body (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Zinc acts as a cofactor in enzymes involved in folate metabolism, including supporting the function of methionine synthase (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Copper is essential for several physiological functions in a child\u0026rsquo;s body, including brain development, glucose metabolism, iron transport, and the maturation of both red and white blood cells (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe frequency of MTHFR (rs1801133 and rs1801131) polymorphism has already been reported in several studies in various countries from different types of disease (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), but not in short stature.The socio-economically weaker countries suffer more from short-stature phenotypes than others.That is, according to reports, the polymorphisms rs1801131 and rs1801133 are more common among South Asians as well as associated with the MTHFR enzyme Activity (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.Thus, building on previous research, we conducted this study on short stature to investigate the association between MTHFR polymorphisms (rs1801131 and rs1801133) and the levels of homocysteine, folate, vitamin B12, as well as the trace elements copper and zinc in the population of Eastern Uttar Pradesh and Bihar.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eSample Selection:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe recruited a total of 280 samples, of which 130 were cases, and 150 were control samples.The study was ethically approved by the ethical committee of the Institute of Medical Sciences, Banaras Hindu University (Ethical No. Dean/2020/EC/2035), and consent was obtained from theparents.\u0026nbsp;Height in centimeters was taken using a calibrated wall-mounted stadiometer (Meddey Technologies Pvt Ltd).\u0026nbsp;Weight in kilogram was taken using a digital weighing machine (IndoSugicals, India). The BMI calculation was based on the formula: weight in kilograms (kg) divided by height in meters (m) squared.\u0026nbsp;Venipuncture blood samples were collected from the Pediatrics Department of IMS BHU in EDTA and Plane vial for DNA isolation and Serum separation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion criteria:\u003c/strong\u003e The study focused on balanced samples of males and females aged 4 to 12 years with short stature. The selection criteria were based on physical and clinical parameters, including height, weight, BMI, and Z-scores, calculated using the WHO Peditools Growth CDC2-20 years charts. Participants were considered to have short stature if their height fell below the 3rd percentile or less than 2 standard deviations below.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion criteria:\u003c/strong\u003eChildren who were excluded include those with chronic and endocrine disorders, as well as those with skeletal abnormalities such as achondroplasia and hypochondroplasia, and those with chromosomal abnormalities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA Extraction and MTHFR Genotyping (rs1801131, rs1801133):\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlood samples were collected in K3 coated EDTA vial. Samples were process according to the kit protocol. DNA was isolated from the Invitrogen kit (catalogue no- K1820-01). Kit lysis buffer was used to lyse RBC and WBC cells, and after lysis, the sample was placed on the column and centrifuged at 1000 RPM for 1 min. After the process was done, the kit protocol followed column washing and elution. DNA quantification was done using spectroscopy (Epoch/2 microplate reader instruments). Whose Purity ratio was 260/280.The rs1801131 and rs1801133 Genotypic polymorphism was done using the kit Applied Biosystems by Thermo Fisher Scientific (TaqMan ®SNP Genotyping Assay). Oligonucleotide primers and hybridization TaqMan probes were designed by Applied Biosystems, Thermo Fisher Scientific, USA. The sequences of oligonucleotide primers assay with assay ID C_1202883_20, the SNP ID rs1801133 is located on chromosome 1 at position 11796321 (based on build GRCh38), exhibiting a G/A transition substitution within the Context sequence GAAAAGCTGCGTGATGATGAAATCG[G/A] CTCCCGCAGACACCTTCTCCTTCAA, and rs1801131AssayIDC_850486_20AAGAACGAAGACTTCAAAGACACTT[G/T]CTTCACTGGTCAGCTCCTCCCCCCA Where Allele 1 is represented by VIC and Allele 2 is represented by FAM (VIC: Victoria green fluorescent protein; FAM: fluorescein amide) in figure3.We had taken 50 ng of pure DNA sample for reaction setup and per reaction sample volume was maintained by following the composition 2X Taqman Assay Buffer \u0026nbsp;5 µl, 20x rs Assay 0.5 µl and DNA template 0.5 µl final volume was maintained by adding 4 µl of nuclease free water to the 10 µl total reaction volume. Real time-PCR was performed by instrument (Bio-red CFX96 real- time PCR). Denaturation was done at (92 \u003csup\u003e0\u003c/sup\u003eC for15 sec) annealing and extension took place at 60 \u003csup\u003e0\u003c/sup\u003eC for 1min and amplification was performed for 40 cycles.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiochemical analysis:\u003c/strong\u003e Serum was isolated at 3,000 rpm for 5 minutes and stored frozen at -80 \u003csup\u003e0\u003c/sup\u003eC until analysis was done. Homocysteine levels were measured by an enzyme-linked immunosorbent assay kit (BT lab catalogueE3292Hu). 50 µl of the sample was added to the ELISA microplate, and incubation was done at 37 \u003csup\u003e0\u003c/sup\u003eC for 45 minutes. After the sample incubation, washing was done three times with a wash buffer, and during this time, a 50 µl biotin-labeled Antibody working solution was prepared. After incubating with the added secondary antibody for 30 minutes, the plate was washed according to the kit protocol, followed by enzyme conjugation to stop the reaction, and the OD was taken at 450 nm. Folic acid detection was done using the BT lab ELISA kit, and the catalogue number was (EA0051Hu). Vitamin B12 was detected using the BT lab Elisa kit, and the catalogue number was (EA0055Hu).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStandard preparation:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStandard solutions for copper (Lot #: 25-154CUX1) and zinc (Lot #: 25-145ZNX1) were used to generate the calibration curves. A stock solution with a concentration of 1000 µg/mL was serially diluted to obtain working standards of 20, 40 and 60 µg/dL. All glassware and plastic containers used in the preparation were thoroughly cleaned with 1% nitric acid, rinsed three times with deionised ultrapure water, and air-dried carefully to prevent contamination\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eZinc and copper measurement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe concentrations of copper (Cu) and zinc (Zn) in the samples were determined using an Atomic Absorption Spectrophotometer (PinAAcle 900 T). To prepare each sample, 200 µL of plasma was mixed with 800 µL of a diluent consisting of 1% nitric acid (HNO₃) and 0.4% Triton X-100 mili-Q water, resulting in a final volume of 1 mL. Measurements were performed using a graphite furnace (GTA-97 unit), with calibration curves that were established from standards prepared in a 1% HNO₃ nanoparticle solution. Element-specific Lumina hollow cathode lamps for copper and zinc (PerkinElmer, manufactured in Singapore) were used during the analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInsilico prediction of Protein structure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 3D structures of Methionine Synthase, Cystathionine Gamma-Lyase, and Cystathionine Beta-Synthase were retrieved from the Protein Data Bank (PDB). These protein structures did not contain bound metal ions in their original form. Water molecules and heteroatoms were removed, missing hydrogen atoms were added, and structures were optimized using Discovery Studio Visualizer 2021.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMetal Binding Docking Using MIB2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe docking of Zn²⁺ (for Methionine Synthase) and Cu²⁺ (for Cystathionine Gamma-Lyase and Beta-Synthase) was performed using the MIB2 (Metal Ion-Binding Site Prediction and Docking) server. MIB2 predicts potential metal-binding sites based on structural alignment with known metalloprotein templates and docks metal ions accordingly. The server outputs the predicted metal-binding residues and estimated binding energies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVisualization and Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe docked complexes obtained from MIB2 were visualized and analyzed using Discovery Studio Visualizer 2021. The key interacting residues involved in metal coordination were identified, and the docking poses were visually confirmed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive statistics were done using GraphPad Prism 8.4.0. Kolmogorov-Smirnov test was used on the Biomarker dataset and was found to be significant, indicating that the data were normally distributed. Data were normally distributed continuous variables biomarker homocysteine, vitamin B12, and folic acid was done by independent samples t-test. A two-tailed P less than 0.05 was considered statistically significant. The Mann-Whitney test was performed to analyze trace element levels between the case and control groups. Two-way Chi-square test was done for Hardy-Weinberg equilibrium to calculate the case's and control's genotype frequency. The comparison of homocysteine across rs1801133 genotypes was performed using a one-way ANOVA, with a p-value of less than 0.05 indicating statistical significance. Additive, dominant, and recessive models for short stature and control groups were analyzed using multiple logistic regressions. Odds ratios, 95% confidence intervals, and p-values were calculated. Spearman correlation analysis was performed to assess the relationships between copper, zinc, homocysteine, folic acid, and vitamin B12 levels. Stepwise regression analysis predicting Cu and Zn was conducted using IBM SPSS 2020.\u003c/p\u003e"},{"header":"Result","content":"\u003cp\u003eThe present study compared the distribution of MTHFR genotypes (C677T and A1298C) and alleles between a short-stature group (N =130) and a control group (N =150). The frequencies of all the genotype and alleles of all the polymorphisms fall under the Hardy- Weinberg equilibrium in the controls. The MTHFR genotype rs1801133 was found to be significant, with a P-value of 0.01. The frequency of the rs1801133 T allele was 37.3% in cases and 24.6% in controls, respectively (odds ratio = 0.609, 95% CI: 0.42\u0026ndash;0.87, P = 0.01). Between the two restriction sites, rs1801133 was significantly associated with short stature between cases and control samples. In contrast, the genotype rs1801131 (A1298C) was not significant, with a P-value of 0.09. The frequency of the C allele for rs1801131 in cases and controls was 31.53% and 26.33%, respectively. Statistically, no significant difference was observed for MTHFR rs1801131 (A1298C) between short-stature cases and controls. The allelic frequency analysis of MTHFR rs1801131 yielded an odds ratio of 0.789 (95% CI: 0.54\u0026ndash;1.13, P = 0.205), indicating no association with short stature in the control group. The genotypic and allele frequency classification of MTHFR rs1801133 (C677T) and rs1801131 (A1298C) among cases and controls is shown in Table 1.\u003c/p\u003e\n\u003cp\u003eIn table.2 in our analysis of rs1801133, significant associations were observed across all models. The additive model yielded an odds ratio (OR) of 1.737 (95% CI: 1.218\u0026ndash;2.477, P = 0.002), indicating that each additional copy of the risk allele increased the odds of the outcome. The dominant model also showed a significant association, with an OR of 1.832 (95% CI: 1.139\u0026ndash;2.946, P = 0.012), suggesting that higher likelihood of the outcome in individuals carrying at least one risk allele. The recessive model demonstrated the strongest association, with an OR of 2.852 (95% CI: 1.296\u0026ndash;6.275, P = 0.009), indicating nearly a threefold increase in odds for individuals with two copies of the risk allele. In contrast, the analysis of rs1801131 showed weaker associations. The additive model produced an OR of 1.229 (95% CI: 0.872\u0026ndash;1.731, P = 0.237), which was not statistically significant. The dominant model approached not significance with an OR of 1.556 (95% CI: 0.969\u0026ndash;2.499, P = 0.066). However, the recessive model did not show a significant association, with an OR of 0.885 (95% CI: 0.421\u0026ndash;1.858, P = 0.746).\u003c/p\u003e\n\u003cp\u003eTable1. \u0026nbsp;MTHFR (rs1801133 and rs1801131) polymorphism in among short stature and controls group.\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"649\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eShort stature group (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(n= 130)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl group (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n= 150)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChi square\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOdds Ratio\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95 % CI)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eMTHFR (C677T)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eGenotype\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e55 \u0026nbsp;(42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e86 \u0026nbsp;(57.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e53 \u0026nbsp;(40.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e54 \u0026nbsp; (36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e9.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e22 \u0026nbsp; (16.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e10 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eAllele\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e163 \u0026nbsp;(62.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e226 \u0026nbsp;(75.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e0.609\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.42 \u0026ndash; 0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e97 \u0026nbsp;(37.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e74 (24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eMTHFR (A1298C)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eGenotype\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e62 \u0026nbsp;(47.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e88 \u0026nbsp;(58.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e54 \u0026nbsp;(41.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e44 \u0026nbsp;(29.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e4.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e14 \u0026nbsp;(10.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e18 \u0026nbsp;(12.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eAllele\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e\u0026nbsp;178 \u0026nbsp; \u0026nbsp; (68.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e220 \u0026nbsp;(73.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e0.789\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.54 \u0026ndash; 1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e0.205\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.142%;\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.2037%;\"\u003e\n \u003cp\u003e82 \u0026nbsp;(31.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.358%;\"\u003e\n \u003cp\u003e80 \u0026nbsp;(26.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.5062%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.7407%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.0494%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eTable2. The MTHFR rs1801133 and rs1801131 frequencies of alleles and genotypes were investigated, consisting of 130 samples of short stature and 150 control samples utilizing additive, dominant and recessive models.\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"729\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRestriction site (rs)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModels\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficient\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOdds ratio\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandard deviation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP- value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95 % Confidence interval \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ers1801133\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ers1801131\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eAdditive\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1.218 \u0026nbsp;\u0026ndash; 2.477\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eDominant\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0.6056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1.832\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1.139 \u0026ndash; 2.946\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eRecessive\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e1.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e2.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e1.296 \u0026ndash; 6.275\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eAdditive\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0.2063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.687\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.872- 1.731\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eDominant\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0.4426\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1.556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.969 \u0026ndash; 2.499\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003eRecessive\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e-0.1221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0.421 \u0026ndash; 1.858\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;In the table.3 \u0026nbsp; significant differences were observed in the levels of homocysteine, folic acid, vitamin B12, zinc, and copper between individuals with short stature (n = 130) and healthy controls (n = 150). Homocysteine levels were markedly higher in the short stature group (17.22 \u0026plusmn; 7.9 nmol/ml) compared to controls (12.84 \u0026plusmn; 3.2 nmol/ml), with a highly significant p-value of 0.001, indicating elevated homocysteine may be associated with short stature. Conversely, levels of folic acid and vitamin B12 were significantly lower in the short stature group (37.45 \u0026plusmn; 10.6 nmol/L and 260.8 \u0026plusmn; 76.18 ng/L, respectively) than in controls (42.75 \u0026plusmn; 7.09 nmol/L and 294.6 \u0026plusmn; 46.9 ng/L), both with p-values of 0.001. Additionally, zinc levels were significantly reduced in the short stature group (90.22 \u0026plusmn; 24.7 \u0026micro;g/dl) compared to controls (100.1 \u0026plusmn; 18.01 \u0026micro;g/dl; p = 0.006), while copper levels were significantly elevated (95.08 \u0026plusmn; 17.06 \u0026micro;g/dl vs. 86.11 \u0026plusmn; 15.2 \u0026micro;g/dl; p = 0.001).\u003c/p\u003e\n\u003cp\u003eTable3. Serum level of homocysteine, folic acid and vitamin B\u003csub\u003e12,\u0026nbsp;\u003c/sub\u003eZinc and Copper in Short stature and control samples.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"659\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eShort stature\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN = 130\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN = 150\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP \u0026ndash; value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHomocysteine\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(nmol/ml)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e17.22 \u0026plusmn; 7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e12.84 \u0026plusmn; 3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFolic acid\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(nmol/L)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e37.45 \u0026plusmn; 10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e42.75 \u0026plusmn; 7.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVitamin B\u003csub\u003e12\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(ng/L)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e260.8 \u0026plusmn; 76.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e294.6 \u0026plusmn; 46.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eZinc \u0026nbsp;(\u0026micro;g/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e90.22 \u0026plusmn; 24.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e100.1 \u0026plusmn; 18.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCopper \u0026nbsp; \u0026nbsp; \u0026nbsp;(\u0026micro;g/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e95.08 \u0026plusmn; 17.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e86.11 \u0026plusmn; 15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData represented with a mean \u0026plusmn; standard deviation and a p-value of less than 0.05 indicates statistical significance.\u003c/p\u003e\n\u003cp\u003eIn table.4\u0026nbsp;The analysis of MTHFR C677T genotypes (CC, CT, TT) in relation to homocysteine, folic acid, and vitamin B12 levels revealed distinct biochemical differences between short stature individuals (n = 130) and controls (n = 150). Among individuals with the CC genotype, no significant differences were observed between short stature and control groups in homocysteine (12.3 \u0026plusmn; 2.7 vs. 11.1 \u0026plusmn; 2.9 nmol/mL; p = 0.103), folic acid (47.06 \u0026plusmn; 3.6 vs. 48.12 \u0026plusmn; 3.4 nmol/L; p = 0.269), or vitamin B12 levels (329.2 \u0026plusmn; 10.9 vs. 333.5 \u0026plusmn; 28.9 ng/L; p = 0.470). Similarly, in the CT genotype group, differences in homocysteine (15.4 \u0026plusmn; 2.8 vs. 14.1 \u0026plusmn; 3.1 nmol/mL; p = 0.082), folic acid (39.6 \u0026plusmn; 2.9 vs. 40.6 \u0026plusmn; 2.4 nmol/L; p = 0.158), and vitamin B12 (280.1 \u0026plusmn; 21.7 vs. 281.1 \u0026plusmn; 27.1 ng/L; p = 0.870) between the two groups were not statistically significant. However, individuals with the TT genotype showed significantly elevated homocysteine levels in the short stature group compared to controls (26.3 \u0026plusmn; 9.6 vs. 14.2 \u0026plusmn; 2.1 nmol/mL; p = 0.001), along with significantly reduced folic acid (22.4 \u0026plusmn; 4.3 vs. 31.3 \u0026plusmn; 7.1 nmol/L; p = 0.001) and vitamin B12 levels (194.4 \u0026plusmn; 27.9 vs. 223.8 \u0026plusmn; 23.17 ng/L; p = 0.001).\u003c/p\u003e\n\u003cp\u003eTable4.Comparison of the MTHFR rs1801133 gene polymorphism with homocysteine,folic acid, and vitamin B12 levels.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"725\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenotype\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMTFHR\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eC677T\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 130\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en= 150\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 173px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHomocysteine\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(nmol/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003evalue\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFolic acid\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(nmol/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVitamin B\u003csub\u003e12\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(ng/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eShort Stature\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003eShort Stature\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003eShort\u003c/p\u003e\n \u003cp\u003eStature\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 55\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en = 86\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e12.3 \u0026plusmn; 2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e11.1 \u0026plusmn; 2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e47.06\u0026plusmn; 3.6\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e48.12\u0026plusmn; 3.4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e329.2 \u0026plusmn; 10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e333.5\u0026plusmn; 28.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.470\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 53\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en = 54\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e15.4 \u0026plusmn; 2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e14.1 \u0026plusmn; 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e39.6\u0026plusmn; 2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e40.6\u0026plusmn; 2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e280.1 \u0026plusmn; 21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e281.1 \u0026plusmn; 27.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.870\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 22\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en = 10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e26.3 \u0026plusmn; 9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e14.2 \u0026plusmn; 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e22.4\u0026plusmn; 4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e31.3\u0026plusmn; 7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e194.4\u0026plusmn; 27.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e223.8 \u0026plusmn; 23.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;In The table.5 MTHFR C677T genotypes and trace element levels (zinc and copper) was examined in individuals with short stature (n = 130) and controls (n = 150). In the CC genotype group, zinc and copper levels did not show significant differences between short stature individuals and controls, with zinc levels at 105.2 \u0026plusmn; 14.7 \u0026micro;g/dl and 108.3 \u0026plusmn; 16.09 \u0026micro;g/dl (p = 0.292), and copper levels at 92.56 \u0026plusmn; 14.17 \u0026micro;g/dl and 89.42 \u0026plusmn; 15.42 \u0026micro;g/dl (p = 0.689), respectively. Similarly, the CT genotype group also showed no significant differences, with zinc levels at 93.45 \u0026plusmn; 24.15 \u0026micro;g/dl in short stature individuals and 96.41 \u0026plusmn; 18.23 \u0026micro;g/dl in controls (p = 0.817), and copper levels at 88.37 \u0026plusmn; 16.55 \u0026micro;g/dl and 84.75 \u0026plusmn; 17.68 \u0026micro;g/dl (p = 0.326), respectively. However, a significant difference was observed in the TT genotype group. Individuals with short stature had markedly lower zinc levels (65.88 \u0026plusmn; 16.69 \u0026micro;g/dl) compared to controls (86.77 \u0026plusmn; 10.65 \u0026micro;g/dl; p = 0.001), and significantly higher copper levels (110.4 \u0026plusmn; 14.94 \u0026micro;g/dl vs. 80.25 \u0026plusmn; 8.03 \u0026micro;g/dl; p = 0.001).\u003c/p\u003e\n\u003cp\u003eTable5.Comparison of the MTHFR rs1801133 gene polymorphism with homocysteine,folic acid, and vitamin B12 levels.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"696\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenotype\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMTFHR\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eC677T\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 130\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en= 150\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZinc \u0026nbsp; \u0026nbsp; (\u0026micro;g/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 199px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCopper \u0026nbsp; (\u0026micro;g/dl)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003eShort Stature\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eShort Stature\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 55\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en = 86\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e105.2 \u0026plusmn; 14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e108.3 \u0026plusmn; 16.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e92.56 \u0026plusmn; 14.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e89.42 \u0026plusmn; 15.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.689\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 53\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en = 54\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e93.45 \u0026plusmn; 24.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e96.41 \u0026plusmn; 18.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.817\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e88.37 \u0026plusmn; 16.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e84.75 \u0026plusmn; 17.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.326\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTT\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 22\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en = 10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e65.88 \u0026plusmn; 16.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e86.77 \u0026plusmn; 10.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e110.4 \u0026plusmn; 14.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e80.25 \u0026plusmn; 8.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Table 6 and Figure 4 the Correlation analysis within individuals carrying the TT genotype of the MTHFR rs1801133 polymorphism (n = 22) revealed significant associations between trace element levels (zinc and copper) and biochemical markers. Homocysteine levels showed a strong negative correlation with zinc (r = -0.805, p = 0.001) and a strong positive correlation with copper (r = 0.747, p = 0.001), suggesting that higher homocysteine levels are associated with reduced zinc and elevated copper. Folic acid demonstrated a moderate positive correlation with zinc (r = 0.471, p = 0.02) and a moderate negative correlation with copper (r = -0.517, p = 0.01). Vitamin B12 levels were positively correlated with zinc (r = 0.749, p = 0.001) and negatively correlated with copper (r = -0.448, p = 0.03).\u003c/p\u003e\n\u003cp\u003eTable.6.Correlation analysis of MTHFR rs1801133 gene polymorphism with levels of homocysteine, folic acid, vitamin B12, zinc, and copper\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"639\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(TT Genotype)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN= 22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 256px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Zinc \u0026nbsp;(\u0026micro;g/dL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 256px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Copper \u0026nbsp; (\u0026micro;g/dL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003eCorrelation coefficient (r)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003eP \u0026nbsp; \u0026nbsp; value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003eCorrelation coefficient (r)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eP \u0026nbsp; \u0026nbsp; value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHomocysteine\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(nmol/ml)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e-0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFolic acid\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(nmol/L)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0.471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e- 0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVitamin B\u003csub\u003e12\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(ng/L)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e-0.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable.7.Regression Analysis Predicting Cu (Copper)\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/95224_ce634422aaf2e7a6/95224_custom_files/img1750087919.png\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The regression analysis predicting copper (Cu) levels revealed that homocysteine was a significant predictor, B = 1.156, SE = 0.229, \u0026beta; = 0.748, t(20) = 5.045, p \u0026lt; 0.001. The model accounted for 56.0% ofthe variance in Cu levels (R\u0026sup2; = 0.560, Adjusted R\u0026sup2; = 0.538), indicating a strong predictive relationship. The overall model was statistically significant, F(1,20) = 25.453, p \u0026lt; 0.0001, suggesting that homocysteine levels are crucial in determining Cu concentrations. The positive regression coefficient implies higher homocysteine levels are associated with increased\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 8. Regression Analysis Predicting Zn (Zinc).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"573\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"bottom\" style=\"width: 142px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 196px;\"\u003e\n \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003eStandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 98px;\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e101.610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e6.670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e15.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003ehomocysteine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e-1.357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e-.786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e-5.691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e55.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e18.705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e2.942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003ehomocysteine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e-.942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e-.546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e-3.584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eB12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e2.623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 573px;\"\u003e\n \u003cp\u003eNote:R\u0026sup2; (Model 1, 2): 0.618, 0.720,Adjusted R\u0026sup2; (Model 1, 2): 0.538, 0.690, F-statistic (Model 1, 2): 32.390, 6.878, p-value (Model 1, 2):\u0026lt; .0001, .017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe regression analysis table provides insights into how variables such as homocysteine and B12 predict zinc (Zn) levels. In Model 1, the constant (intercept) is significantly positive (B = 101.610, t = 15.233, p \u0026lt; .0001), suggesting that, when homocysteine is zero, zinc levels are predicted to be around 101.61. Homocysteine, however, has a significant negative effect on zinc levels (B = -1.357, t = -5.691, p \u0026lt; .0001), with the negative coefficient indicating that higher homocysteine levels are associated with lower zinc levels. In Model 2, the constant is again significantly positive (B = 55.027, t = 2.942, p = .008), while homocysteine continues to show a negative relationship with zinc (B = -0.942, t = -3.584, p = .002). Additionally, vitamin B12 (B = 0.239, t = 2.623, p = .017) has a positive and significant effect on zinc, suggesting that higher B12 levels are linked to higher zinc levels. The R\u0026sup2; values (0.618 for Model 1 and 0.720 for Model 2) indicate that the models explain approximately 61.8% and 72% of the variability in zinc levels, respectively. The adjusted R\u0026sup2; values (0.538 and 0.690) show that these models are fairly robust. The significant F-statistics (32.390 for Model 1 and 6.878 for Model 2) further support the overall significance of the models, with p-values indicating that both models are highly statistically significant which was shown in table.8 and figure.6.\u003c/p\u003e\n\u003cp\u003eThe docking results from MIB2 provided binding energy values and predicted residues involved in the coordination of Zn\u0026sup2;⁺ and Cu\u0026sup2;⁺ ions to the target proteins. The docked complexes were successfully visualized in Discovery Studio. The findings are summarized in the table below:\u003c/p\u003e\n\u003cp\u003eTable. 9. This table shows the Zn\u0026sup2;⁺ and Cu\u0026sup2;⁺ binding energies and interacting residues in the enzymes Methionine Synthase, Cystathionine Gamma-Lyase, and Cystathionine Beta-Synthase.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eComplex Name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBinding Energy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBinding Residues\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMethionine Synthase \u0026ndash; Zn\u0026sup2;⁺\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ndash;7.74 kcal/mol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCYS260, CYS323, CYS324, ASN287\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCystathionine Gamma-Lyase \u0026ndash; Cu\u0026sup2;⁺\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ndash;6.64 kcal/mol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eARG161, GLU131\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCystathionine Beta-Synthase \u0026ndash; Cu\u0026sup2;⁺\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ndash;6.72 kcal/mol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eARG132, ASP129\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAmong the docked complexes, Methionine Synthase with Zn\u0026sup2;⁺ showed the highest binding affinity (\u0026ndash;7.74 kcal/mol), suggesting a strong coordination between the zinc ion and cysteine/asparagine residues. The copper-binding proteins also showed favorable binding energies and conserved interaction residues predicted by MIB2 in table.9.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study investigated the association between MTHFR polymorphisms rs1801133 (C677T) and rs1801131 (A1298C) with short stature in 130 cases and 150 controls. All genotypic distributions adhered to Hardy-Weinberg equilibrium among controls. The rs1801133 T allele was significantly more prevalent in short-stature individuals (37.3%) than in controls (24.6%), with an odds ratio (OR) of 0.609 and \u003cem\u003eP\u003c/em\u003e = 0.01, suggesting it as a potential risk factor for short stature. This polymorphism demonstrated significant associations across additive (OR = 1.737, \u003cem\u003eP\u003c/em\u003e = 0.002), dominant (OR = 1.832, \u003cem\u003eP\u003c/em\u003e = 0.012), and recessive (OR = 2.852, \u003cem\u003eP\u003c/em\u003e = 0.009) models, reinforcing its potential role in growth impairment. Conversely, rs1801131 did not exhibit a significant association, with the C allele frequency at 31.53% in cases versus 26.33% in controls (OR = 0.789, \u003cem\u003eP\u003c/em\u003e = 0.205). The additive, dominant, and recessive models for rs1801131 were also non-significant. These findings align with recent studies indicating that the MTHFR C677T variant may influence conditions related to growth and development. For instance, a case report identified a novel MTHFR mutation associated with hyperhomocysteinemia, presenting as tall stature and skeletal abnormalities, underscoring the enzyme's role in growth regulation (27). Additionally, research has linked the MTHFR C677T variant to altered folate metabolism, which is crucial for DNA synthesis and methylation processes vital for normal growth (28). \u0026nbsp;The biochemical analysis in the present study revealed significant alterations in key metabolic parameters among individuals with short stature compared to healthy controls, suggesting a potential link between micronutrient imbalances and impaired growth. Elevated homocysteine levels in the short stature group (17.22 ± 7.9 nmol/ml vs. 12.84 ± 3.2 nmol/ml; \u003cem\u003ep\u003c/em\u003e = 0.001) may reflect disrupted folate and vitamin B12 metabolism, as both were significantly lower in cases (37.45 ± 10.6 nmol/L and 260.8 ± 76.18 ng/L, respectively) than controls (42.75 ± 7.09 nmol/L and 294.6 ± 46.9 ng/L; \u003cem\u003ep\u003c/em\u003e = 0.001), supporting the role of these vitamins in one-carbon metabolism and growth. Similar associations have been observed in previous studies, where elevated homocysteine and low B-vitamin levels were linked to growth retardation and developmental delays (29). Moreover, the study found significantly reduced zinc and elevated copper levels in the short stature group, which aligns with existing literature highlighting zinc deficiency as a risk factor for growth failure and the antagonistic relationship between zinc and copper in maintaining metabolic balance (30,31). These findings underscore the importance of monitoring and addressing nutritional and metabolic imbalances in children with growth impairments.Recent studies havecorroborated these associations relationship between MTHFR polymorphisms, homocysteine, folic acid, and vitamin B12 levels in pregnant women.They found significant associations between vitamin B12 and folic acid levels with homocysteine concentrations, where lower serum levels of these vitamins were linked to higher homocysteine levels.Interestingly, no significant association was observed between MTHFR genetic polymorphisms and serum homocysteine levels, likely due to folic acid and vitamin B12 supplementation during pregnancy, which may mitigate the mutation's effects (32)\u0026nbsp;. Additionally, a study highlighted a significant association between the MTHFR C677T TT genotype and vitamin B12 deficiency.They reported that individuals with the TT genotype had a higher prevalence of vitamin B12 deficiency compared to those with CC or CT genotypes.This deficiency was also linked to elevated homocysteine levels and endothelial dysfunction, emphasizing the clinical significance of this genetic variant. These findings underscore the importance of monitoring and managing vitamin B12 and folic acid levels in individuals with the MTHFR C677T TT genotype to mitigate potential health risks (33).In individuals carrying the TT genotype of the MTHFR rs1801133 polymorphism, a significant correlation was observed between trace elements and biochemical markers, indicating a genotype-dependent interplay affecting metabolic balance. Elevated homocysteine levels were strongly associated with decreased zinc and increased copper levels, consistent with findings that MTHFR C677T homozygosity impairs enzyme function, leading to hyperhomocysteinemia and redox imbalance (34,35). The observed correlations of folic acid and vitamin B12 with zinc and copper further highlight the interconnectedness of one-carbon metabolism and trace element homeostasis. Prior studies have shown that zinc plays a critical role in methionine synthase function and DNA methylation, processes disrupted in folate and B12 deficiency (36). Moreover, excess copper has been linked to oxidative stress, which can exacerbate folate cycle dysfunction in genetically predisposed individuals (37). A recent study reported altered zinc and copper levels in individuals with MTHFR polymorphisms, reinforcing the metabolic vulnerability conferred by the TT genotype. These associations suggest that maintaining optimal trace element levels might mitigate metabolic disturbances and should be considered in nutritional strategies for individuals with MTHFR C677T homozygosity (38).The regression model demonstrated that homocysteine is a significant predictor of copper (Cu) levels, suggesting a mechanistic link between homocysteine metabolism and copper homeostasis. With a positive regression coefficient (B = 1.156, β = 0.748, \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.001), the model accounted for 56.0% of the variance in copper levels (R² = 0.560), indicating that elevated homocysteine concentrations are strongly associated with increased copper accumulation. This relationship may be explained by the pro-oxidant nature of both homocysteine and copper. Homocysteine can induce oxidative stress by generating reactive oxygen species (ROS) and reducing the availability of antioxidant defenses, while copper, especially in its free ionic form, participates in Fenton-like reactions that exacerbate oxidative damage (39,40). The findings align with previous reports indicating a biochemical crosstalk between copper metabolism and one-carbon metabolism pathways, with potential implications for vascular, neurological, and metabolic disorders (41, 42). This model reinforces the need to consider trace element dynamics in conditions associated with elevated homocysteine.The regression analysis highlights the interconnected roles of homocysteine and vitamin B12 in modulating zinc (Zn) levels, offering key insights into trace element metabolism. Model 1 reveals a strong inverse association between homocysteine and zinc (B = -1.357, \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.0001), consistent with studies suggesting that elevated homocysteine disrupts zinc absorption and increases oxidative stress, which may deplete zinc reserves (43,44). In Model 2, this negative association remains (B = -0.942, \u003cem\u003ep\u003c/em\u003e = 0.002), while vitamin B12 emerges as a significant positive predictor of zinc levels (B = 0.239, \u003cem\u003ep\u003c/em\u003e = 0.017). This aligns with prior findings indicating that B12 plays a role in DNA synthesis, red blood cell formation, and proper absorption of trace elements like zinc (45,46). The high R² values in both models (0.618 and 0.720) reinforce the predictive strength and clinical relevance of these variables in regulating zinc status. These findings contribute to a growing body of evidence emphasizing the interaction between one-carbon metabolism and trace element regulation, with implications for nutritional interventions in populations at risk for micronutrient deficiencies and metabolic disorders (47,48).\u003c/p\u003e\n\u003cp\u003eBased on our biochemical findings in TT genotype individuals—characterized by elevated homocysteine levels, low vitamin B12 and folic acid, decreased zinc, and increased copper we proposed a hypothesis that disruptions in trace element balance may compromise the activity of key enzymes in homocysteine metabolism. Specifically, we hypothesized that excess copper may negatively impact the enzymes of the transsulfuration pathway cystathionine beta-synthase (CBS) and Cystathionine Gamma-Lyase\u003cstrong\u003e\u0026nbsp;(\u003c/strong\u003eCGL), while zinc deficiency could impair methionine synthase (MS), a key enzyme in the remethylation pathway in figure.1.\u003c/p\u003e\n\u003cp\u003eTo test this, we performed molecular docking to explore how Cu²⁺ and Zn²⁺ interact with these enzymes at a structural level. \u0026nbsp;Docking analysis revealed that Cu²⁺ binds to the CGL enzyme with a binding energy of –6.64 kcal/mol, primarily interacting with residues ARG161 and GLU131. For the CBS enzyme, Cu²⁺ showed a binding energy of –6.72 kcal/mol at residues ARG132 and ASP129. These interactions suggest that copper may interfere with the structural stability or catalytic activity of these enzymes, potentially contributing to impaired transsulfuration and homocysteine accumulation.In support of the role of zinc in remethylation, docking studies with methionine synthase and Zn²⁺ demonstrated a strong binding affinity of –7.74 kcal/mol, with key interactions at residues CYS260, CYS323, CYS324, and ASN287. These results suggest that zinc plays a stabilizing role in maintaining methionine synthase structure and function.Overall, our molecular docking findings provide structural insights that support our hypothesis: elevated copper and reduced zinc levels may disrupt the normal function of homocysteine-metabolizing enzymes, contributing to hyperhomocysteinemia in individuals with the TT genotype.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn our study, we found that the MTHFR rs180113 polymorphism was significantly associated with homocysteine levels. Individuals with the TT genotype exhibited higher homocysteine levels and lower levels of folic acid and B12 compared to those with CT and CC genotypes. Additionally, individuals with the TT genotype showed higher level of copper and lower level of Zinc in short stature group in compression of control group suggesting a potential link between trace elements and homocysteine metabolism.The increased homocysteine levels observed in individuals with short stature compared to controls further support the possible involvement of homocysteine metabolism in growth regulation. Moreover, the imbalance of trace elements, particularly copper and zinc appears to influence homocysteine levels. Given the multifactorial nature of short stature and metabolic disturbances further studies involving larger and more diverse cohorts are essential to validate and strengthen these associations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical committee approval:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eName of the ethical committee:\u003c/strong\u003e Institute of Medical Science, Banaras Hindu University\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe want to extend our sincere gratitude to Multi-Disciplinary Research Units (MRUs) Laboratory, a grant by ICMR-Department of Health Research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies involving human participants were reviewed and approved by Ethics Committee of the Institutional Ethical committee before starting the study (Ethical No. Dean/2020/EC/2035)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll research procedures were approved by and in accordance with relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe detailed datasets analyzed during the current study are available with the corresponding author. In the future, it will be made available on reasonable request. Data are however available from the authors upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRS, and AS conceived and designed the project. AKY, AA, NKS, SV and ST performed all operations. AKM analysed the data and SM, PD, SS, JY drew the figures. ABY and RS wrote the manuscript. AS, AA, AKM and NKS revised the manuscript. All authors contributed to the article and approved the submitted version.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eGrunauer M, Jorge AA. Genetic short stature. 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European Journal of Clinical Nutrition. 2023 Dec; 77(12):1105-12.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Homocysteine, MTHFR, Short stature, Genotyping, Copper, Zinc","lastPublishedDoi":"10.21203/rs.3.rs-6516790/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6516790/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Human height generally follows a normal distribution; thus, short stature is defined as height below the 3rd percentile or 2 standard deviations (SD) from the mean. Homocysteine metabolism, which involves folate and vitamin B12, is regulated by the methylenetetrahydrofolate reductase (MTHFR) enzyme. This study aimed to investigate the association of MTHFR polymorphisms with trace elements (copper and zinc), homocysteine, folic acid, and vitamin B12 in children with short stature.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A total of 280 participants (130 short stature cases and 150 healthy controls), aged 4–12 years, were included. Serum homocysteine, folic acid, and vitamin B12 were measured using ELISA. MTHFR polymorphisms (rs1801133 and rs1801131) were genotyped using TaqMan® SNP Genotyping Assay via RT-PCR. Copper and zinc levels were measured by atomic absorption spectrophotometry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The MTHFR rs1801133 polymorphism showed a significant association with short stature, with individuals carrying the TT genotype exhibiting higher homocysteine levels (26.3 ± 9.6 µmol/L), and lower folic acid (22.4 ± 4.3 ng/mL) and B12 levels (194.4 ± 27.9 pg/mL) compared to controls (p \u0026lt; 0.001). The TT genotype was also associated with higher copper (110.4 ± 14.94 µg/dL) and lower zinc levels (65.88 ± 16.69 µg/dL) in cases versus controls (p \u0026lt; 0.001). No significant association was observed for rs1801131.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The MTHFR rs1801133 (TT genotype) is associated with elevated homocysteine, altered trace elements, and increased risk of short stature. These findings highlight the role of genetic and nutritional factors in growth regulation.\u003c/p\u003e","manuscriptTitle":"Association of MTHFR Gene Variants (rs1801133 and rs1801131) with Serum Trace Elements Copper and Zinc and Biochemical Parameters (Homocysteine, Folic Acid, and Vitamin B12) in Individuals with Short Stature","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-17 09:24:11","doi":"10.21203/rs.3.rs-6516790/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2588f4e1-20a1-4fac-97be-f0bdd1d166aa","owner":[],"postedDate":"June 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-23T14:08:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-17 09:24:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6516790","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6516790","identity":"rs-6516790","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}