Abstract
Background
Clinical and genetic studies have suggested that immune dysregulation and neuroinflammation are involved in the pathogenesis of schizophrenia. Peripheral laboratory markers are accessible indicators linked to systemic inflammation and immune function. Genetic studies have demonstrated that blood parameters are highly heritable. Therefore, the aim of this study was to analyze the association between blood parameters and IL10, TNF, TLR2, and TLR6 gene polymorphisms in Mexican patients with schizophrenia.
Methods
We included 236 Mexican patients with schizophrenia. Peripheral blood samples were obtained in the early morning, prior the breakfast, from each participant. Complete blood count was analyzed. Genomic DNA was extracted, and genotyping was performed using TaqMan Discrimination assay of IL10 (rs1554286), TNF (rs1800629), TLR2 (rs7656411), and TLR6 (rs5743827). Association analyses between blood parameters and genotypes of the four genetic variants were performed using chi-square tests and ANOVA with Tukey’s post-hoc multiple comparisons.
Results
We observed higher monocyte levels (F = 5.57; p = 0.004) and monocyte-lymphocyte ratio (F = 5.49; p = 0.004) in patients carrying the GG genotype of rs7656411/TLR2 compared with TT or TG genotype carriers. Additionally, we observed a high frequency of the G allele of rs1800629/TNF, showing a low platelet count compared with carriers of the A allele (χ2 = 8.6, p = 0.003; OR = 3.82; CI, 1.46–9.96). Furthermore, we were unable to detect any gene-gene interaction in the analysis of MPV and platelet count after 1000-fold permutation testing.
Conclusions
Our findings indicate that blood parameter levels may be affected by genetic variants of TNF and TLR2 genes, indicating a potential role for innate immune response activation in schizophrenia in the Mexican population. Further studies with larger cohorts and comprehensive genetic analyses are essential to validate these findings and clarify the role of innate immune genes in schizophrenia.
Keywords: TNF, TLR2, Schizophrenia, Inflammation, Immune, Association study
Background
Schizophrenia is a complex and chronic disorder characterized by the presence of psychopathological symptoms classified as positive, negative, and cognitive disturbances. This disorder has a lifetime prevalence of 1% [1]. Although the cause of this psychiatric condition remains unknown, it has been suggested that immune dysregulation and neuroinflammation are involved in the pathogenesis of schizophrenia [2]. Schizophrenia and other pathologies within the psychotic phenotype have been associated with peripheral immunological abnormalities. Previous meta-analysis reported increased monocytes and neutrophils as well as lymphocytes in patients with schizophrenia in early stages of the disorder, eosinophils showed inconclusive results regarding their potential association with schizophrenia [3, 4]. Furthermore, the ratios of neutrophils/lymphocytes, monocytes/lymphocytes, and platelets/lymphocytes in blood were significantly elevated, which is consistent with the findings reported in the literature, indicating a broad activation of the immune system in patients with schizophrenia [4].
Platelet parameters provide a simple and accessible biochemical model to study the role of inflammation in schizophrenia and other mental disorders due to their essential role in the inflammatory cascade; their surface is lined with many proinflammatory receptors, such as major histocompatibility complex, toll-like receptors (TLRs), receptors for advanced glycation end products (RAGE), CD40L, and P-selectin [5]. Platelets can also interact with various immune cells, including B-cells, T-cells, macrophages, neutrophils, endothelial cells, natural killer cells, and dendritic cells. These interactions can trigger a range of immune-related responses, positioning platelets as modulators of the innate immune response in various system cells [6].
Platelet count (PLT) and mean platelet volume (MPV) are widely accessible indicators of thrombosis and systemic inflammation, reflecting the size and reactivity of circulating platelets [7], autoimmune diseases, and infections [8]. Platelets and neurons have been reported to demonstrate similar abnormalities in several neuropsychiatric diseases, including Alzheimer’s disease, Parkinson’s disease, major depressive disorder, and schizophrenia [9]. In the case of psychiatric disorders, several studies have observed significantly high PLT and MPV values in patients with schizophrenia and first-psychotic episode [10–13]. However, another study found no significant differences in MPV in patients with first-psychotic episode compared to healthy controls [14].
Twin and family studies have demonstrated that platelet parameters are highly heritable, estimating heritability of 0.84 for PLT and 0.75 for MPV, suggesting the presence of genetic factors related to these traits [15–17]. Genome-wide association studies (GWAS) have identified genetic variants associated with PLT and MPV [18–24]. In addition, PLT and MPV are tightly controlled within narrow physiological ranges that differ by ethnicity, suggesting population-specific contributions [18, 25]. Interestingly, a GWAS performed in Hispanic/Latino populations identified independent signals within PLT-associated regions previously identified in European populations [18].
Lin and colleagues performed a meta-analysis of GWAS in schizophrenia and identified overrepresented biologically plausible pathways, particularly the signaling pathway of Toll- like receptors (TLRs) [25]. Several studies have associated genetic variants of interleukin 10 (IL10), tumor necrosis factor (TNF), TLR2, and TLR6 with schizophrenia in several populations (Table 1) [26–34].
Table 1.
Association studies between the genes analyzed and schizophrenia
| Study | Gene/Variant | Population | Findings |
|---|---|---|---|
| Bocchio Chiavetto et al., 2002 [26] |
IL-10 −1082 G/A, − 819 T/C, − 592 C/A |
European population; 106 cases/143 controls | Significant increase of GCC in schizophrenic patients compared with controls |
| Qin et al., 2013 [27] |
TNF-α rs1800629 |
Caucasian and Asian population 4340 cases/5745 controls |
No association with schizophrenia |
| He et al., 2022 [28] |
TNF-α rs1800629, rs361525, |
Multiethnic meta-analysis 6465 cases/6866 controls |
Significant association (especially in Asians) |
| Kang et al., 2022 [29] |
TNF-α rs1800629 |
Korean population 55 cases |
A-allele carriers associated with impaired fronto-temporal connectivity in the risk to schizophrenia |
| Alfimova et al., 2022 [30] |
TNF-α rs1800629 |
Russian population 546 cases |
Interaction between childhood adversity and in the pathogenesis to schizophrenia |
| Sotelo-Ramírez et al., 2023 [31] |
TLR2 rs3804099, rs7656411, rs5743709. TLR6 rs5743810, rs3775073, rs5743827 |
Mexican population; 191 cases/217 controls | Significant association between TLR2/rs5743709 and schizophrenia |
| Mikhalitskaya et al., 2023 [32] |
IL-10 rs180087, rs1800872, rs1800896, rs6676671 TNF-α rs1799724, rs1800629 |
Multiethnic case-control narrative review | Association between IL-10 and schizophrenia |
| Gonzalez-Castro et al., 2024 [33] |
IL-10 rs1800871, rs1800872, rs1800896 |
Multiethnic meta-analysis; 22 case-control studies, n = 4993 cases/5195 controls | IL-10 confers an increased risk of schizophrenia. |
| Datsjerdi et al., 2025 [34] |
TNF-α rs1800629 |
Asian and Caucasian population 7624 cases/8933 controls |
No association with schizophrenia |
Recent advances in the field of immunopsychiatry have highlighted the role of innate immune receptors and proinflammatory signaling pathways in the pathogenesis of schizophrenia [5, 35]. TLRs recognize pathogen and damage-associated molecular patterns and activate intracellular cascades such as the NF-κB and MAPK pathways, leading to the transcription of key inflammatory mediators like TNF-α and other cytokines like IL-10 [5]. Dysregulation of these pathways has been reported in peripheral immune cells [36, 37] and postmortem brain tissue from patients with schizophrenia [38, 39], suggesting that chronic low-grade inflammation may be involved in disease progression. Atypical immune responses in schizophrenia support the hypothesis that genetic variation in these components may influence susceptibility to the disorder [40], as well as associated inflammatory traits such as changes in blood parameters [11]. This biological framework provides a rationale for investigating polymorphisms in genes such as IL10, TNF, TLR2, and TLR6, which are involved in immune signaling and inflammation.
Therefore, this study aimed to identify associations between genetic variants of IL10, TNF, TLR2, TLR6, and blood parameter levels in Mexican patients with schizophrenia.
Methods
Participants
The study included 236 Mexican patients recruited from Hospital Psiquiatrico Fray Bernardino Álvarez who met the DSM-5 criteria for schizophrenia, as determined by the Spanish version of the Mini International Neuropsychiatric Interview (MINI-5). Participants were Mexican mestizos with a family background of at least three generations born in Mexico, aged 18 years or older, with an age of onset < 60 years. Blood biometric studies were obtained from all patients during their first episode of psychosis. Patients with leukocytosis of > 11,000 cells/ml, a body mass index above 30, pregnancy or breastfeeding, or chronic or degenerative diseases such as rheumatoid arthritis, cancer, or autoimmune diseases were excluded from the study. The investigation was conducted following the latest version of the Declaration of Helsinki. All patients provided written informed consent at the time of recruitment, which was obtained after the nature of the procedures had been fully explained. The Institutional Ethics Committee of Hospital Psiquiatrico Fray Bernardino Álvarez approved the study.
Analysis of the blood parameters
Peripheral blood (10 mL) was collected in EDTA-containing Vacutainer tubes® (BD) in the early morning, prior the breakfast, from each participant. Complete blood count was analyzed using the impedance method with Coulter ac-T 5diff hematological equipment (Beckman). The reference range for leukocytes and platelets were as follow: lymphocytes: 1-3.20 103/mcL, monocytes: 0.30–1.10 103/mcL, neutrophils: 1.7–7.8 103/mcL and platelets: 152–348 103/mcL.
Indices of neutrophil/limphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), and platelet/lymphocyte ratio (PLR) were obtained of the participants. Patients were grouped based on platelet count: high (> 250 cells/mL) or low (< 250 cells/mL). Additionally, patients were classified by mean platelet volume: high (> 8.7 fL) or low (< 8.7 fL) [14].
SNP Selection
We examined the polymorphisms rs7656411 (TLR2), rs5743827 (TLR6), rs1554286 (IL10), and rs1800629 (TNF) using data from PubMed, the UCSC Genome Browser (human, GRCh/hg38), and the Genetic Association Database. These variants were functional polymorphisms based on nucleotide changes within regulatory regions previously associated with RNA expression levels, inflammatory processes, schizophrenia, or other psychiatric disorders.
Genotyping
Genomic DNA was extracted from peripheral blood samples using the Flexigene DNA kit (Qiagen, Minneapolis, MN). Genotyping was conducted with custom TaqMan assays for polymorphisms in IL10 (rs1554286, C_8828812_10), TNF (rs1800629, C_7514879_10), TLR2 (rs7656411, C_29420880_10), and TLR6 (rs5743827, C_1180651_20) genes. The allele-specific TaqMan assay method employed a Real Time PCR StepOne™ System (Applied Biosystems Inc.). Each 7 µL reaction contained 50 ng genomic DNA, 1X TaqMan Universal Master Mix, and 20X SNP Genotyping Assay Mix (Applied Biosystem s Inc.). The reaction protocol involved initial denaturation at 95 °C for one minute, followed by 40 PCR cycles of denaturation at 95 °C for 15 s and annealing at 60 °C for 1 min.
Gene–gene interaction analysis
To explore potential synergistic effects between genetic variants on hematological parameters, a gene–gene interaction (G×G) analysis was performed using the Multifactor Dimensionality Reduction (MDR) software version 3.0.2 [41]. This approach allows the identification of non-linear interactions among multiple loci without requiring main effects. For each model, the testing balanced accuracy (TBA) and cross-validation consistency (CVC) were calculated to estimate predictive performance. Statistical significance was assessed through a 1000-fold permutation test. Models with the highest CVC and TBA values were prioritized, and a p-value < 0.0001 was considered statistically significant. MPV and platelet count were examined separately.
Statistical analysis
Demographic and clinical characteristics were analyzed using descriptive statistics, including means, standard deviations, and percentages. Association analyses between blood parameters and genotypes of the four genetic variants were performed using chi-square tests or ANOVA with Tukey’s post-hoc multiple comparisons. Chi-square tests were also used to analyze associations between genotype and allele frequencies with high or low PLT and MPV. Statistical analyses were conducted using RStudio version 2023.06.1 + 524. Bonferroni correction was applied for multiple testing (four polymorphisms corrected at p < 0.0125).
Results
The demographic and clinical characteristics of the sample are presented in Table 2.
Table 2.
Demographic and clinical characteristics of the sample
| Characteristic | Patients (n = 236) |
|---|---|
| Age, mean (SD) | 33.4 (9.7) |
| Sex, n (%) | |
| Females | 91 (38.9) |
| Males | 143 (61.1) |
| Age of onset (years), mean (SD) | 23.2 (7.8) |
| Duration of untreated psychosis (months), mean (SD) | 37.1 (69.9) |
| Family history of schizophrenia, n (%) | 28 (11.8) |
| Family history of depression, n (%) | 11 (4.7) |
| Family history of suicide behavior, n (%) | 5 (2.1) |
| Blood parameters, mean (SD), 103/mcL | |
| Lymphocytes | 2.4 (1.6) |
| Monocytes | 0.5 (0.5) |
| Neutrophils | 3.8 (1.4) |
| Platelets | 246.3 (65.5) |
| NLR | 1.7 (1.2) |
| MLR | 0.2 (0.2) |
| PLR | 117.9 (83.5) |
| MPV, fL | 9 (1.3) |
NLR Neutrophil/lymphocyte ratio, MLR Monocyte/lymphocyte ratio, PLR Platelet/lymphocyte ratio, MPV Mean platelet volume
The study sample revealed that there was a higher proportion of males than females, which is consistent with the reported patterns in schizophrenia patients. In addition, the blood parameters in the patients were within normal ranges (Table 2). The analysis of the mean and standard deviation of blood parameters according to genotypes of the polymorphisms of IL10, TNF, TLR2, and TLR6 are shown in Table 3.
Table 3.
Association of blood parameters and genetic variants analyzed in patients with schizophrenia
| Characteristics, mean (SD) | Genotypes | Statistics | ||
|---|---|---|---|---|
| IL10/rs1554286 | GG | GA | AA | |
| Lymphocytes | 2.2 (0.7) | 2.6 (2.1) | 2.3 (0.7) | F = 0.91, p = 0.4 |
| Monocytes | 0.5 (0.2) | 0.6 (0.7) | 0.5 (0.2) | F = 0.87, p = 0.41 |
| Neutrophils | 3.8 (1.4) | 3.7 (1.3) | 4.1 (1.7) | F = 1.57, p = 0.21 |
| Platelets | 247.5 (68.5) | 250.2 (60.8) | 235 (72.4) | F = 0.94, p = 0.39 |
| NLR | 1.8 (0.9) | 1.7 (1.4) | 1.9 (1.1) | F = 1.09, p = 0.33 |
| MLR | 0.2 (0.1) | 0.2 (0.3) | 0.2 (0.1) | F = 0.59, p = 0.55 |
| PLR | 120 (54.1) | 120.6 (106) | 108.7 (46.1) | F = 0.37, p = 0.68 |
| MPV | 8.9 (1.3) | 9 (1) | 9.3 (1.8) | F = 1.37, p = 0.25 |
| TNF/rs1800629 | GG | GA | AA | |
| Lymphocytes | 2.4 (1.6) | 2.8 (0.9) | - | t = −1.5, p = 0.14 |
| Monocytes | 0.5 (0.5) | 0.5 (0.1) | - | t = −0.06, p = 0.94 |
| Neutrophils | 3.8 (1.4) | 4.1 (1.7) | - | t = −0.65, p = 0.52 |
| Platelets | 244.9 (65.3) | 266.8 (67.7) | - | t = −1.16, p = 0.26 |
| NLR | 1.7 (1.2) | 1.7 (1.1) | - | t = 0.26, p = 0.79 |
| MLR | 0.2 (0.2) | 0.2 (0.1) | - | t = 1.41, p = 0.16 |
| PLR | 118.8 (85.3) | 104.6 (43.6) | - | t = 1.09, p = 0.28 |
| MPV | 9 (1.3) | 9.1 (0.7) | - | t = −0.29, p = 0.79 |
| TLR2/rs7656411 | TT | TG | GG | |
| Lymphocytes | 2.5 (1.9) | 2.2 (0.8) | 2.3 (0.7) | F = 0.58, p = 0.55 |
| Monocytes | 0.5 (0.2) | 0.6 (0.7) | 1.1 (1.6) | F = 5.57, p = 0.004 |
| Neutrophils | 3.8 (1.5) | 3.9 (1.3) | 3.9 (1.8) | F = 0.21, p = 0.8 |
| Platelets | 244.9 (63.5) | 250 (68.9) | 236.9 (78.8) | F = 0.23, p = 0.79 |
| NLR | 1.7 (1.3) | 1.91 (1.1) | 1.7 (0.7) | F = 0.78, p = 0.45 |
| MLR | 0.2 (0.1) | 0.2 (0.2) | 0.4 (0.6) | F = 5.49, p = 0.004 |
| PLR | 114.3 (92.7) | 125.9 (63.1) | 113 (62.9) | F = 0.5, p = 0.6 |
| MPV | 9.2 (1.4) | 8.8 (1.1) | 8.8 (0.9) | F = 2.18, p = 0.11 |
| TLR6/rs5743827 | CC | CT | TT | |
| Lymphocytes | 2.3 (0.8) | 2.9 (3.3) | 2.5 (0.6) | F = 2.25, p = 0.1 |
| Monocytes | 0.5 (0.6) | 0.5 (0.2) | 0.5 (0.1) | F = 0.15, p = 0.85 |
| Neutrophils | 3.9 (1.4) | 3.6 (1.4) | 4.3 (1.6) | F = 0.73, p = 0.48 |
| Platelets | 244.7 (66.8) | 251.8 (62.9) | 249.7 (54.7) | F = 0.22, p = 0.8 |
| NLR | 1.8 (1.3) | 1.5 (0.9) | 1.8 (0.7) | F = 1.53, p = 0.21 |
| MLR | 0.2 (0.2) | 0.2 (0.1) | 0.2 (0.05) | F = 0.65, p = 0.52 |
| PLR | 121.2 (90.5) | 107.1 (54) | 104.1 (34.1) | F = 0.61, p = 0.54 |
| MPV | 9 (1.1) | 9.1 (1.9) | 9.1 (0.7) | F = 0.23, p = 0.79 |
NLR Neutrophil/lymphocyte ratio, MLR Monocyte/lymphocyte ratio, PLR Platelet/lymphocyte ratio, MPV Mean platelet volume
Bolded text indicates a p-value below 0.0125 (4 SNPs/0.05)
Genetic analysis
We observed higher monocyte levels (F = 5.57; p = 0.004) and monocyte-lymphocyte ratio (F = 5.49; p = 0.004) in patients carrying the GG genotype of rs7656411/TLR2 compared with TT or TG genotype carriers (Table 3).
Furthermore, genotype and allele frequencies of polymorphisms in the IL10, TNF, TLR2, and TLR6 genes were analyzed in patients with high and low PLT and MPV (Table 4). We observed a high frequency of the G allele of rs1800629/TNF, which showed a low PLT compared with carriers of the A allele (χ2 = 8.6, p = 0.003; OR = 3.82; CI, 1.46–9.96).
Table 4.
Genotype and allele frequencies of gene variants analyzed concerning high or low count of platelets and mean platelet volume
| Genotype | χ2 | p | Alleles | χ2 | p | ||||
|---|---|---|---|---|---|---|---|---|---|
| Platelet count IL10 | |||||||||
| rs1554286 | GG | GA | AA | G | A | ||||
| Low | 38 (0.28) | 69 (0.51) | 28 (0.21) | 0 | 1 | 145 (0.54) | 125 (0.46) | 0.01 | 0.96 |
| High | 28 (0.28) | 51 (0.51) | 21 (0.21) | 107 (0.54) | 93 (0.46) | ||||
| TNF | |||||||||
| rs1800629 | GG | GA | AA | G | A | ||||
| Low | 129 (0.96) | 6 (0.04) | 0 | 1.3 | 0.25 | 264 (0.98) | 6 (0.02) | 8.6 | 0.003 |
| High | 92 (0.92) | 8 (0.08) | 0 | 184 (0.92) | 16 (0.08) | ||||
| TLR2 | |||||||||
| rs7656411 | TT | TG | GG | T | G | ||||
| Low | 86 (0.64) | 43 (0.32) | 6 (0.04) | 1.0 | 0.58 | 215 (0.8) | 55 (0.2) | 0.4 | 0.52 |
| High | 66 (0.66) | 32 (0.32) | 2 (0.02) | 164 (0.82) | 36 (0.18) | ||||
| TLR6 | |||||||||
| rs5743827 | CC | CT | TT | C | T | ||||
| Low | 105 (0.78) | 26 (0.19) | 4 (0.03) | 0.02 | 0.98 | 236 (0.87) | 34 (0.13) | 0.01 | 0.89 |
| High | 77 (0.77) | 20 (0.20) | 3 (0.03) | 174 (0.87) | 26 (0.13) | ||||
| MPV | |||||||||
| IL10 | |||||||||
| rs1554286 | GG | GA | AA | G | A | ||||
| Low | 29 (0.35) | 41 (0.49) | 13 (0.16) | 3.8 | 0.23 | 99 (0.6) | 67 (0.4) | 3.7 | 0.054 |
| High | 36 (0.24) | 76 (0.52) | 35 (0.24) | 148 (0.5) | 146 (0.5) | ||||
| TNF | |||||||||
| rs1800629 | GG | GA | AA | G | A | ||||
| Low | 80 (0.96) | 3 (0.04) | - | 0.79 | 0.37 | 163 (0.98) | 3 (0.02) | 1.3 | 0.24 |
| High | 136 (0.93) | 11(0.07) | - | 283 (0.96) | 11 (0.04) | ||||
| TLR2 | |||||||||
| rs7656411 | TT | TG | GG | T | G | ||||
| Low | 49 (0.59) | 30 (0.36) | 4 (0.05) | 2.4 | 0.29 | 128 (0.77) | 38 (0.23) | 2.1 | 0.14 |
| High | 99 (0.67) | 45 (0.31) | 3 (0.02) | 243 (0.83) | 51 (0.17) | ||||
| TLR6 | |||||||||
| rs5743827 | CC | CT | TT | C | T | ||||
| Low | 64 (0.77) | 17 (0.2) | 2 (0.03) | 0.2 | 0.91 | 145 (0.87) | 21 (0.13) | 0.03 | 0.85 |
| High | 113 (0.77) | 29 (0.2) | 5 (0.03) | 255 (0.87) | 39 (0.13) | ||||
MPV Mean platelet volume
Bolded text indicates a p-value below 0.0125 (4 SNPs/0.05)
G×G interaction
Genetic variants were evaluated by testing GxG interaction models to determine their combined effect on MPV and platelet count. Although different combinations were evaluated, none of the models showed statistically significant results after 1000-fold permutation testing. The best performing models for MPV were IL-10 and TLR2, which showed TBA > 0.579 and high CVC (10/10). For, Platelet count the top model was IL-10, TNF, TLR2, TLR6, also showing high CVC (10/10) and TBA above 0.505. After permutation analysis, all these models failed to achieve statistical significance (Table 5).
Table 5.
Gene–gene interaction model for platelet count and MPV in patients with schizophrenia
| Models | TA | CVC | OR (95% IC) | p |
|---|---|---|---|---|
| MPV | ||||
| IL-10, TLR2 | 0.579 | 10/10 | 2.12 (1.22–3.55) | ns |
| IL-10, TLR2, TLR6 | 0.523 | 7/10 | 2.34 (1.35–4.05) | ns |
| IL-10, TNF, TLR2, TLR6 | 0.503 | 10/10 | 2.61 (1.48–4.61) | ns |
| Platelet count | ||||
| TLR2, TLR6 | 0.432 | 6/10 | 1.52 (0.88–2.62) | ns |
| IL-10, TLR2, TLR6 | 0.504 | 9/10 | 2.09 (1.21–3.6) | ns |
| IL-10, TNF, TLR2, TLR6 | 0.505 | 10/10 | 1.05 (0.18–5.96) | ns |
IL-10: rs1554286. TNF: rs1800629. TLR2: rs7656411. TLR6: rs5743827
TA Test accuracy, CVC cross-validation consistency
1000-fold permutation. ns not statistically significant
Discussion
Recent studies have shown increased interest in the immune system’s role in schizophrenia pathophysiology [42–44]. However, no research has examined parameter levels and their relationship with candidate genes in Mexican schizophrenia patients.
Blood parameters in our study sample were within normal ranges, though we lacked a healthy control group for comparison. Reference values can vary by sex, age, and ethnicity [17]. Sex-related differences in hematological parameters have been widely reported in other populations. Large cohort studies have shown that women have higher platelet counts than men, but men may have slightly higher MPV values. Hormonal, genetic, and physiological factors are believed to be responsible for these differences, which has led to the recommendation of using sex-specific reference ranges for platelet indices [45, 46]. Including a control group in future studies is necessary to examine differences specific to schizophrenia.
This study aimed to investigate four candidate genes involved in innate immune response in Mexican schizophrenia patients. Numerous GWAS have identified genes related to inflammation and immune response in schizophrenia [47, 48]. To our knowledge, this is the first genetic study reporting associations between TNF and TLR2 gene polymorphisms and blood parameters in Mexican schizophrenia patients.
To our knowledge, this is the first genetic study to report associations between polymorphisms in the TNF and TLR2 genes and blood parameters in Mexican patients with schizophrenia. We observed a differential genotype distribution of rs7656411/TLR2 and blood parameters in schizophrenia patients. Carriers of the GG genotype showed higher mean monocyte counts and monocyte/lymphocyte ratios compared to TT homozygotes and heterozygotes. Özdin et al. reported elevated neutrophil/lymphocyte and monocyte/lymphocyte ratios in schizophrenia patients during psychotic episodes [49].
Studies in European populations have shown decreased TLR1, TLR2, TLR4, and TLR6 gene expression in schizophrenia patients [50, 51]. Genetic polymorphisms located in regulatory regions, such as promoters, enhancers, or untranslated regions (UTRs), may influence the transcriptional activity of these genes, potentially altering their expression levels. Variants that affect transcription factor binding sites, epigenetic regulation, or mRNA stability can lead to reduced gene expression, which may contribute to impaired innate immune responses. In this context, the polymorphisms analyzed in our study may participate in the downregulation of TLR gene expression observed in schizophrenia, potentially modulating susceptibility to the disorder through altered inflammatory signaling pathways [52].
The rs7656411 variant of the TLR2 gene is in the 3´UTR region, potentially affecting polymerase binding and altering gene expression levels in monocytes of schizophrenia patients [53].
Elevated monocyte counts have been documented in patients with first-episode psychosis compared to healthy controls, strengthening the idea of immune system dysfunction [54]. Monocytes are a crucial part of the innate immune system, serving as the primary defense against invading pathogens. During an active infection, monocytes synthesize cytokines like IL-1, IL-6, and TNF-α, which have been reported to be altered in patients with schizophrenia [55]. These cytokines trigger signaling cascades that promote the differentiation of monocytes into macrophages and activate the adaptive immune response. Macrophages infiltrating the central nervous system (CNS) transform into microglia, which help contain potential infections and tissue damage [56]. Microglial cells play an important role in modulating neuronal synapses, synaptic pruning, and white matter connections [38]. Microglial-mediated inflammatory processes have been proposed as a potential mechanism for the structural brain changes identified in schizophrenia [57, 58]. With this understanding, platelets, monocytes, and microglial cells express TLRs, crucial proteins in initiating the innate immune response. The activation of the TLR signaling pathway triggers the synthesis of proinflammatory cytokines, including TNF-α, which has been found altered in patients with schizophrenia [42, 59, 60].
We found a significant association between allele A of rs1800629/TNF and a high PLT count compared to patients with a low count. Previous studies suggested that TNF-α is associated with the activation of dopamine pathways. Interestingly, dopamine dysfunction has been suggested in the etiology of schizophrenia. Alterations in the gene expression of peripheral TNF-α have been observed in patients with schizophrenia, supporting evidence that inflammatory cytokines are involved in the etiology of schizophrenia [61–63].
To our knowledge, no studies have reported a genetic association between TNF-α and PLT in patients with schizophrenia. The rs1800629 variant of TNF is in a non-coding region. However, these variant flanks two regions corresponding to cis-regulatory elements, which could modify the expression levels of the TNF gene and surrounding genes [53]. A search in the UCSC Genome Browser (human, GRCh/hg38) to identify the transcription factor binding sites at the location of the rs1800629 variant revealed that ZNF320 and ZNF281 can bind at this site [53]. These two transcription factors have been associated with the transcriptional regulation of multiple genes, including TNF [64–66]. Previous studies have shown that TNF-α plays a central role in hematopoiesis and inflammation by modulating the differentiation and proliferation of megakaryocytes, thereby influencing platelet production [67].
We suggest that the variant of rs1800629/TNF may influence the differential expression levels of PLT in patients with schizophrenia.
Gene–gene interaction analysis was performed to investigate potential synergistic effects of IL-10, TNF, TLR2, and TLR6 polymorphisms on hematological traits, specifically MPV and platelet count in patients with schizophrenia. Despite the presence of interaction models that showed high CVC = 10/10 and good TBA > 0.57 for MPV, none of them achieved statistical significance after 1000-fold permutation testing.
According to these findings, the combined effects of the evaluated polymorphisms do not have a significant impact on MPV or platelet count in the studied cohort. The polygenic and multifactorial nature of schizophrenia could be reflected by the absence of statistically significant GxG interactions, in which the contribution of individual variants or their interactions may be subtle or context dependent [2]. It is possible that environmental, epigenetic, or other regulatory factors may have a more significant effect on modulating these hematological traits in individuals who are affected [17].
It has been reported that significant GxG interactions involving TLR and cytokine genes have been observed in the context of schizophrenia susceptibility [68]. No studies have examined their influence on peripheral biomarkers like platelet parameters. Our findings highlight the complexity of immuno-genetic contributions to schizophrenia and underscore the need for larger, multi-ethnic cohorts and integrative analyses that consider both genetic and non-genetic factors.
Furthermore, no previous studies have described a direct relationship between the genomic location of variants in TNF, TLR2, TLR6, or IL10 and peripheral blood parameters such as PLT or MPV in this population. These findings provide novel evidence of a potential genetic influence on hematological and inflammatory traits in schizophrenia, particularly in understudied populations such as Mexicans.
The identification of genetic variants that influence both immune signaling and hematological profiles contributes to a better understanding of the complex interplay between the immune system and schizophrenia pathophysiology. Given the key roles of TNF and TLRs in inflammation and innate immunity, these associations suggest that immune dysregulation caused by genetics may affect peripheral markers such as platelet count, which are easily accessible in clinical settings. The presence of population-specific variants and their interaction with environmental factors may help explain ethnic differences in clinical presentation, prognosis, or treatment response in schizophrenia.
Future studies should explore the functional consequences of these variants, such as their impact on gene expression, cytokine levels, or protein activity, as well as their potential utility as biomarkers for disease susceptibility or immune status in patients with schizophrenia. Expanding this line of research may offer new avenues for personalized approaches to diagnosis, prognosis, and immunomodulatory treatment strategies in psychiatric disorders.
Limitations
Our study has several limitations. First, we did not include a healthy control group for comparison with patients with schizophrenia, which could have provided information on changes in blood parameters. Second, we had a small sample size of patients with schizophrenia; therefore, the associations observed should be taken with caution. Third, the study analyzed four genes implicated in neuroinflammation; however, the imbalance of the inflammatory cascade in patients with schizophrenia implicates several genes.
Conclusion
Our findings suggest that genetic variants of the TNF and TLR2 genes may influence blood parameter levels in schizophrenia patients, highlighting the potential involvement of innate immune response activation in the disorder’s pathophysiology. The observed association between the rs7656411/TLR2 variant and monocyte levels, as well as the rs1800629/TNF variant and platelet counts, supports the hypothesis that immune dysregulation may contribute to schizophrenia. Given the critical role of monocytes, microglial cells, and proinflammatory cytokines in neuroinflammation, these genetic associations may provide insights into the immune-related mechanisms underlying schizophrenia. Further studies with larger cohorts and comprehensive genetic analyses are essential to validate these findings and clarify the role of innate immune genes in schizophrenia. Understanding these genetic influences may contribute to the development of novel therapeutic strategies targeting immune system dysfunction in schizophrenia.
Acknowledgements
We thank all the patients who participated in this study for their valuable contribution, which was essential to advancing our understanding of the genetic and immune factors involved in schizophrenia. Dr. Rosa Mara Osiris Pazarán and Dr. Miguel Portugal Márquez are acknowledged for the support they have provided.
Abbreviations
- DSM-5
Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition
- GWAS
Genome-Wide Association Study
- IL-10
Interleukin-10
- MINI-5
Mini International Neuropsychiatric Interview, Fifth Version
- MLR
Monocyte/lymphocyte ratio
- MPV
Mean platelet volume
- NLR
Neutrophil/lymphocyte ratio
- PCR
Polymerase chain reaction
- PLR
Platelet/lymphocyte ratio
- PLT
Platelet count
- RAGE
Receptors for advanced glycation end products
- TLR-2
Toll-like receptor-2
- TLR-6
Toll-like receptor-6
- TNF
Tumor necrosis factor
Authors’ contributions
HCR: conceptualization, validation, writing-original draft, supervision and funding acquisition; CESR: conceptualization, data analysis, data curation, writing-original draft; JJP: validation, data curation, revision of the manuscript; MASJ: data analysis; PMC: validation, data curation. BC: conceptualization and design, revision of the manuscript, supervision and funding acquisition.All authors reviewed the manuscript.
Funding
This work was supported by Instituto Nacional de Psiquiatria Ramon de la Fuente Muñiz (No. IC-16028.0) and Hospital Psiquiatrico Fray Bernardino Álvarez.
Data availability
Data will be available on request.
Declarations
Ethics approval and consent to participate
The study was conducted according with the Declaration of Helsinki. All participants signed informed consent. The institutional ethics committee approved the study protocol (CEI/C/017/2016).
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Héctor Cabello-Rangel and Sotelo-Ramírez Carlo Esteban contributed equally to this work.
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Data Availability Statement
Data will be available on request.