The importance of genetic polymorphisms in stroke risk lies in their contribution to understanding individual susceptibility, guiding risk prediction, unraveling pathophysiological mechanisms, informing treatment strategies, and fostering the development of personalized approaches to stroke prevention and management. In this study, we evaluated the association of exon variant rs1800470 of TGF-β1 gene with the risk of stroke using a meta-analysis method. Our results showed that this genetic variation is correlated with the increased risk of stroke. Additionally, we determined that this variation is correlated with the stroke risk in Asian population and this may imply that the effect of this genetic variation is based on race. Also, almost all analyzes revealed that our meta-analysis shows no evidence of publication bias and this can be a reason of the reliability of our meta-analysis.

Recently, two meta-analyses similar to our study have been conducted [25, 26]. In the study by Braidy et al. (2022), a meta-analysis was carried out on the relationship between the rs1800470 variation and the stroke risk in the Asian population. This study was more limited compared to ours, as it focused solely on the Asian population and included only six studies. Additionally, they did not perform a subgroup analysis but applied precise inclusion and exclusion criteria, similar to our study, for selecting the articles. Their results slightly differed from ours, which could be due to the exclusion of the studies by Liang [19] and Kumar et al. [22] from their meta-analysis. However, in the study by Peng et al. [26], a more comprehensive analysis was conducted on three polymorphisms: rs1800468, rs1800469, and rs1800470, and the risk of stroke. Regarding the rs1800470 polymorphism, they examined five genetic models, whereas we analyzed seven models. Their inclusion and exclusion criteria were nearly the same as ours and were comprehensive. The slight difference in their results compared to ours was in the number of articles included, as they incorporated eight articles into their meta-analysis. Similar to us, they also carried out a subgroup analysis by ethnicity and genotyping techniques. Additionally, an earlier meta-analysis by Peng et al. in 2013 included the first six studies as our paper. In their meta-analysis, they concluded that because of the small sample size and significant heterogeneity between studies, more large-scale, well-designed prospective studies are necessary [27].

Inflammation plays a crucial role in the pathophysiology of ischemia. An ischemic stroke occurs when there is a blockage or reduction in blood supply to part of the brain, resulting in a lack of oxygen and nutrients. Lack of blood flow leads to ischemia, which triggers a complex cascade of events including inflammatory responses [28]. Ischemic events in the brain result in the activation of various immune cells, such as microglia and peripheral immune cells that infiltrate the injured area. Activated immune cells secrete pro-inflammatory mediators such as cytokines and chemokines into the surrounding tissue. These mediators help recruit additional immune cells to the site of injury [29]. Ischemic stroke can disrupt the blood–brain barrier, enabling immune cells and inflammatory substances to penetrate the brain more easily. This further exacerbates the inflammatory response and may contribute to secondary brain damage [30]. Ischemia leads to the production of reactive oxygen species, which are highly reactive compounds that can trigger oxidative stress and lead to harm in cellular structures. This oxidative stress in turn contributes to inflammation and nerve damage. In general, the role of cytokines in brain inflammatory processes is very prominent [31].

The TGF-β1 molecule is a versatile cytokine that contributes a complex role in inflammation. TGF-β1 is part of the TGF-β family and has a role in various pathological and physiological procedures including immune regulation, tissue development, wound healing, and inflammation. Its role in inflammation can be both anti-inflammatory and pro-inflammatory, which varies depending on the context and stage of the inflammatory response [32]. TGF-β1 has immunosuppressive effects and can prevent the proliferation and activation of various immune cells, such as B and T cells. Also, for the differentiation and maintenance of regulatory T cells, which have a crucial role in immune tolerance and inhibition of excessive immune responses is crucial [33]. On the other hand, TGF-β1 stimulates the production of extracellular matrix proteins and leads to tissue regeneration. In addition, TGF-β1 can influence the production of other cytokines in the inflammatory environment. It may increase the production of certain anti-inflammatory cytokines while preventing the secretion of pro-inflammatory cytokines. The effects of TGF-β1 are highly context-dependent. In acute inflammation or in the early phases of damage, it may have anti-inflammatory effects by promoting tissue repair and regulating immunity [33, 34]. However, in chronic inflammation, TGF-β1 can contribute to fibrosis and tissue damage. Also, this molecule plays a role in relieving inflammation by promoting the clearing of apoptotic cells and tissue repair processes. In addition, the rs1800470 SNP is positioned in the signal peptide region, which impacts the TGFβ1 secretion [35]. As mentioned, the TGF-β1 molecule plays a major role in inflammation, and any changes in the structure and expression of this molecule may increase the risk of inflammatory disorders and interfere with stroke pathology [36, 37].

Genetic polymorphisms based on their location on the gene may change the structure and expression of a gene. If the genetic variants are in upstream or downstream regions, it can change gene expression because these mentioned regions have binding elements and can change the binding of regulatory proteins. On the other hand, the polymorphisms that exist in the structural part of the gene may be exonic or intronic, which in any case can affect the splicing process and change the function of the gene. Meanwhile, exon polymorphisms, if they are of missense type, could impact the protein function and structure. The rs1800470 polymorphism is also an exonic variant, so it may affect gene expression and protein structure [38, 39]. Examining the impacts of genetic varieties on gene function experimentally is a difficult and time-consuming task, so computational approaches can be helpful in this field [40]. Therefore, it is suggested to investigate the effects of rs1800470 variation on gene function with an in silico approach.