Genetic studies

A genetic variation (SNP rs1800629) in the TNF alpha gene located on chromosome 6, is named TNFα − 308 G/A because it involves a Guanine (G) that can be replaced by Adenine (A) at the 308th nucleotide position. The G allele is more common (reference allele), while the A allele is less frequent (alternative allele). You can find more details about this specific SNP on the NCBI website using the provided ID, as shown in Supplementary Table 1 (S1).

Hardy Weinberg equilibrium for studied SNPs

Assessing whether the TNF-α − 308 G/A (rs1800629) gene variant follows Hardy–Weinberg equilibrium in two groups: control (n = 100) and ALL (n = 100), likely representing patients with a specific disease, as shown in Table 1. The table shows the observed and expected genotype frequencies for GG, GA, and AA variants in each group. The analysis compares these frequencies and finds a good fit (p-values > 0.05) between observed and expected values in both groups. This result suggests that the genetic distribution of TNF-α − 308 G/A is stable within each group and is not influenced by external factors such as selection bias or non-random mating.

Table 1 Assessment of Hardy Weinberg equilibrium for TNF-α genotypes

The subjects were selected randomly from population in Dakahlia Governorate in Egypt. They were unrelated. Regarding rs1800629, among ALL group, 17 GG, 55 GA and 28 AA were observed, while among control group, 48 GG, 48 GA and 4 AA were observed.

Baseline dataDemographic data and age range considerations

The study cohort comprised 100 individuals diagnosed with ALL with a mean age of 9.62 years, ranging from 2 to 17 years. This age distribution includes both the typical peak incidence age range of 2–5 years and extends into older children and adolescents. Table 2 provides a comparison of age and gender between the ALL group and the healthy control group.

Table 2 Comparison of age and gender among ALL patients and control groups

Although the peak incidence of pediatric ALL is commonly observed between 2–5 years of age, our study also included older children up to 17 years. This broader age range was chosen to ensure a comprehensive understanding of ALL across different developmental stages. It is acknowledged that clinical presentations of ALL may differ between younger children and adolescents. However, the inclusion of older children in this study provides valuable insights into the potential variability of ALL presentation and progression in a broader age spectrum.

The distribution of gender within this group comprised 64% males and 36% females. Additionally, an equivalent number of 100 healthy control subjects were included, carefully matched for both age and gender with the ALL cases, as shown in Table 2. The age and gender distributions were carefully matched between the ALL cases and control subjects to minimize confounding variables. The statistical analysis confirmed that there were no significant differences in age or gender between the ALL cases and control subjects, ensuring that these factors did not bias the results.

By assessing the weight of the 100 ALL patients. The average patient weighs 31.54 kg (kg) with a standard deviation of 8.26 kg, indicating some variation around this value. Half the patients weigh more than 32.0 kg (median), while the other half weigh less. There's a total weight range of 32 kg (from 14.0 kg to 46.0 kg) within the ALL group, as shown in Table 3. Weight loss, a common clinical characteristic in many diseases, was investigated in the 100 ALL patients. As shown in Table 3, 61% (n = 61) of the patients did not report weight loss, while 39% (n = 39) did. The distribution of immunophenotypes in a group of 100 patients diagnosed with ALL is a laboratory technique used to identify specific cell surface proteins on leukemia cells, which helps classify the leukemia subtype. The immunophenotype in 100 ALL patients. Most (82%) have B-cell ALL, where leukemia originates from B lymphocytes, while 18% have T-cell ALL, arising from T lymphocytes. This distribution might reflect the overall higher prevalence of B-cell ALL or be specific to the study population, as shown in Table 3.

Table 3 Weight and immunophenotyping among ALL patients group

The blood cell profile of the studied 100 ALL patients reveals several key findings. Elevated white blood cell count (TLC): The average white blood cell count is significantly high (11.59 × 10^9/L) with a narrow range (9.00 – 12.92 × 10^9/L). Reduced red blood cell count (RBC), hemoglobin, and platelets: Compared to normal ranges, these values are lower on average (RBC: 3.79 × 10^12/L, Hemoglobin: 8.75 g/dL, Platelets: 78.93 × 10^9/L). Increased percentage of blasts: Both peripheral blood and bone marrow show elevated blast percentages, indicating the presence of immature leukemia cells (Peripheral: 26.87%, Bone marrow: 81.98%). The bone marrow has a wider range of blast percentages (44.00 – 105.00%) compared to peripheral blood, as shown in Supplementary Table 2.

The Rhesus factor (Rh) distribution among the 100 ALL patients shows that all 100 patients (100%) are Rh positive, and none were Rh negative, as shown in Supplementary Table 3. The study might have unknowingly recruited participants who are more likely to be Rh positive. This could happen if the recruitment process favored a specific geographic location or blood bank where Rh positivity is more prevalent. With only 100 participants, the study might not be large enough to capture the true distribution of Rh factors in the ALL population. A larger sample size would provide more statistically significant results. It's important to note that Rh factor itself is not known to be a risk factor for ALL. More research is needed to understand the reasons behind this observed distribution in this particular study.

TNFα − 308 among studied groups

TNF alpha gene polymorphism (− 308 G/A) was investigated using RFLP-PCR and classified as wild-type (GG), heterozygous carrier (GA), and homozygous variant (AA) genotypes. Results of PCR after gel electrophoresis are shown in Fig. 1.

Fig. 1

Agarose gel electrophoresis for TNF genotypes: ladder size marker (M) 50–1000 bp. Lane 1,3,5,7,9,13,15 A allele at 154 bp, Lane 2,4,6,10,11,12,14 G allele at 224 bp

Supplementary Fig. 1, 2 & 3 show agarose gel electrophoresis results for TNF genotypes in various exposure group.

Investigating a variation in the TNF-alpha gene (rs1800629) between 100 ALL patients and 100 control subjects, the ALL group has a significantly higher frequency of the A allele (associated with variant AA and GA genotypes) compared to the control group (p-value < 0.001). This suggests a potential association between the TNF-alpha gene variation and ALL risk. Both dominant (GA + AA vs GG) and recessive (AA vs GG + GA) models show significant associations (p-value < 0.001). This means carrying either one or two copies of the A allele increases the risk of ALL compared to having only the G allele (considered the reference). The odds ratios (OR) further quantify this risk, with the AA genotype conferring the highest risk (OR = 5.983) compared to GG. The frequency of the A allele is substantially higher in the ALL group (55.5%) compared to controls (28.0%). This again suggests a potential role for this allele in ALL development, as shown in Table 4 and Fig. 2.

Table 4 TNFα − 308 G/A (rs1800629) among ALL patients and control groupFig. 2

TNFα − 308 G/A (rs1800629) among ALL patients and control group

Association of TNFα − 308 with other parameters

This study of 100 ALL patients explored a potential link between the TNF-alpha gene variation (rs1800629) and weight loss, a common clinical presentation. Patients with the AA genotype (identified in Table 4 as the highest risk group) experienced weight loss at a higher proportion (42.9%) compared to those with GG (11.8%) or GA (45.5%). The TNF-alpha gene plays a role in inflammation, and the A allele might be associated with increased inflammation. This chronic inflammation could contribute to weight loss in some ALL patients. Notably, weight loss distribution differed significantly between rs1800629 genotypes (p = 0.040), with the highest incidence observed in the AA group, followed by GA and GG, as shown in Supplementary Table 4.

A variation in a specific TNFα gene (rs1800629) affects lab results in ALL patients as shown in Supplementary Table 5. The table divides patients into three groups based on their gene variation (GG, GA, AA) and shows various blood test results like platelet count, hemoglobin levels, and bone marrow blasts percentage. For most tests, there are no statistically significant differences (p-value > 0.05) between the genetic groups, meaning the gene variation likely doesn't influence those specific lab values in ALL patients.

The link between a TNFα gene variation (rs1800629) and the type of ALL in patients as shown in Supplementary Table 6. The table categorizes patients by their gene variation (GG, GA, AA) and shows the distribution of B-cell ALL (B-ALL) and T-cell ALL (T-ALL). While there's a trend of increasing T-ALL with more A alleles (GG to AA), the statistical test (p-value = 0.141) suggests that the IPT was not affected by rs1800629 genotypes (p > 0.05), and more data may be needed to confirm a definitive association.

The FAB subtypes (L1 and L2) are further delineated, and the percentage distribution of each genotype within these subtypes is provided. Notably, in FAB subtype L1, the GG genotype shows a higher prevalence (94.1%) compared to GA (56.4%) and AA (57.1%), emphasizing the potential role of this genetic variant in FAB subtype differentiation among ALL patients, as shown also in Supplementary Fig. 4.

TGF-β among studied groups

A comparative analysis of Transforming Growth Factor-beta (TGF-β) levels between a control group (n = 100) and patients with ALL (n = 100). The TGF-β concentrations are provided in ng/mL, and the mean ± SE values for the control group (77.45 ± 2.03) and ALL patients (18.89 ± 1.22) highlight a substantial difference in TGF-β levels. A Mann–Whitney U test was conducted, resulting in a statistically significant p-value (p < 0.001), indicating a significant disparity in TGF-β concentrations between the two groups. The median TGF-β levels for the control group and ALL patients are reported as 77.50 and 15.0 ng/mL, respectively, further emphasizing the considerable reduction in TGF-β levels in ALL patients. The range of TGF-β concentrations in the control group spans from 21.0 to 152.0 ng/mL, while the range for ALL patients is narrower, ranging from 4.90 to 52.0 ng/mL. These findings suggest a potential association between TGF-β levels and the presence of ALL, underscoring the relevance of TGF-β in the context of leukemia pathophysiology, as shown in Table 5 and Fig. 3.

Table 5 Comparison of TGF-β among ALL patients and control groupFig. 3

Boxplot for TGF-β among ALL patients and control group

The association between the TNFα − 308 G/A (rs1800629) polymorphism and Transforming Growth Factor-beta (TGF-β) levels within the control group as shown in Supplementary Table 7. The table is organized based on the different genotypes (GG, AG, AA) of the TNFα − 308 G/A variant, and corresponding TGF-β concentrations are presented in ng/mL. The mean TGF-β levels for each genotype are reported as 73.96 (GG), 81.63 (AG), and 69.25 (AA). Although there is a numerical difference in mean TGF-β concentrations among the genotypes, the p-value (0.167) suggests that this difference is not statistically significant. The standard errors (SE) provide information on the variability of the mean estimates, and the medians, minimum, and maximum values offer insights into the distribution and range of TGF-β concentrations within each genotype. Overall, the table indicates that there is no significant association between the TNFα − 308 G/A polymorphism and TGF-β levels in the control group, as the p-value exceeds the conventional threshold of significance (p > 0.05).

An analysis of the association between the TNFα − 308 G/A (rs1800629) polymorphism and TGF-β levels within the ALL group as shown in Supplementary Table 8 and Fig. 4. The table is structured by different genotypes (GG, AG, AA) of the TNFα − 308 G/A variant, and corresponding TGF-β concentrations are provided in ng/mL. The mean TGF-β levels for each genotype are reported as 25.68 (GG), 17.85 (AG), and 16.81 (AA). The p-value of 0.026 suggests a statistically significant association between the TNFα − 308 G/A polymorphism and TGF-β levels in the ALL group. Standard errors (SE) offer insights into the precision of the mean estimates, and medians, minimum, and maximum values provide information on the distribution and range of TGF-β concentrations within each genotype. Notably, the lower mean TGF-β levels in the AG and AA genotypes compared to GG suggest a potential impact of the TNFα − 308 G/A polymorphism on TGF-β regulation in the context of ALL, emphasizing the relevance of this genetic variant in leukemia pathophysiology.

Fig. 4

TGFB level between TNFα − 308 G/A (rs1800629) among ALL group

Prediction of ALL susceptibility

The providing results from regression analysis aimed at predicting susceptibility to ALL, as shown in Table 6. The table is divided into univariable and multivariable analyses, each with columns displaying p-values, odds ratios (OR), and their corresponding 95% confidence intervals (CI) for the variables TGF-β and TNFα − 308. In the univariable analysis, both TGF-β and TNFα − 308 show statistically significant associations with ALL susceptibility, as indicated by low p-values (< 0.001). The odds ratio for TGF-β is 0.891 with a 95% CI of 0.858–0.925, while TNFα − 308 has an odds ratio of 2.536 with a 95% CI of 1.713–3.754. In the multivariable analysis, both variables continue to exhibit significant associations with ALL susceptibility, with p-values < 0.001 for TGF-β and 0.014 for TNFα − 308. The odds ratios are adjusted to 0.997 (95% CI: 0.996–0.998) for TGF-β and 1.128 (95% CI: 1.090–1.268) for TNFα − 308. These findings suggest that TGF-β and TNFα − 308 are independent predictors of ALL susceptibility, emphasizing their potential roles in the development of the disease.

Table 6 Regression analysis for prediction of ALL susceptibility

As illustrated in Table 7 and Fig. 5, TGF-β shows remarkable diagnostic accuracy for Acute Lymphoblastic Leukemia (ALL). Table 7 presents critical diagnostic parameters, including the Area Under the Curve (AUC), 95% Confidence Interval (CI), optimal cutoff value, sensitivity, and specificity. With an AUC of 0.995 within a 95% CI range of 0.973 to 1, TGF-β demonstrates an outstanding ability to differentiate ALL cases from controls. The optimal cutoff of ≤ 52 yields an impressive diagnostic performance, achieving 100% sensitivity and 96% specificity. These findings underscore the high reliability of TGF-β for accurately identifying ALL cases, particularly due to its exceptional sensitivity, which ensures true positives, and its high specificity, minimizing false positives.

Table 7 Validity of TGF-β for diagnostic ability of ALLFig. 5

ROC of TGF-β for discrimination between ALL cases and control subjects

While ALL diagnosis is conventionally achieved through routine hematologic and bone marrow assessments, the robust performance of TGF-β in our study highlights its potential role beyond primary diagnostics. The data support exploring TGF-β as a supplementary marker that could elucidate mechanisms in leukemia pathogenesis, contribute to prognostic assessments, and potentially guide targeted therapeutic interventions. This analysis substantiates TGF-β’s consistency and strength as a biomarker in clinical settings, suggesting its value not only in diagnostic applications but also as a promising avenue for future therapeutic and prognostic use.

The Receiver Operating Characteristic (ROC) curve for TGF-β reveals high diagnostic accuracy with an AUC of 0.995. The best cutoff value of 52 achieves 100% sensitivity and 96% specificity for distinguishing ALL cases from healthy controls.